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You searched for +publisher:"Georgia Tech" +contributor:("Ahmed, Shabbir"). Showing records 1 – 30 of 63 total matches.

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Georgia Tech

1. Ramachandran, Thiagarajan. Algorithmically induced architectures for multi-agent system.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 The objective of this thesis is to understand the interactions between the computational mechanisms, described by algorithms and software, and the physical world, described by… (more)

Subjects/Keywords: Cyber-physical systems; Model predictive control; MPC; Optimization

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APA (6th Edition):

Ramachandran, T. (2016). Algorithmically induced architectures for multi-agent system. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55019

Chicago Manual of Style (16th Edition):

Ramachandran, Thiagarajan. “Algorithmically induced architectures for multi-agent system.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/55019.

MLA Handbook (7th Edition):

Ramachandran, Thiagarajan. “Algorithmically induced architectures for multi-agent system.” 2016. Web. 18 Oct 2019.

Vancouver:

Ramachandran T. Algorithmically induced architectures for multi-agent system. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/55019.

Council of Science Editors:

Ramachandran T. Algorithmically induced architectures for multi-agent system. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55019


Georgia Tech

2. Zou, Jikai. Large scale multistage stochastic integer programming with applications in electric power systems.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

 Multistage stochastic integer programming (MSIP) is a framework for sequential decision making under uncertainty, where the uncertainty is modeled by a general stochastic process, and… (more)

Subjects/Keywords: Multistage stochastic integer programming; Stochastic dual dynamic programming; Power systems; Generation expansion planning; Unit commitment

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APA (6th Edition):

Zou, J. (2017). Large scale multistage stochastic integer programming with applications in electric power systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59102

Chicago Manual of Style (16th Edition):

Zou, Jikai. “Large scale multistage stochastic integer programming with applications in electric power systems.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/59102.

MLA Handbook (7th Edition):

Zou, Jikai. “Large scale multistage stochastic integer programming with applications in electric power systems.” 2017. Web. 18 Oct 2019.

Vancouver:

Zou J. Large scale multistage stochastic integer programming with applications in electric power systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/59102.

Council of Science Editors:

Zou J. Large scale multistage stochastic integer programming with applications in electric power systems. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59102


Georgia Tech

3. Peppanen, Jouni Aleksi. Improving distribution system model accuracy by leveraging ubiquitous sensors.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 To enable advanced distribution automation schemes with ubiquitous distributed energy resources, it is imperative to increase distribution system modeling accuracy and detail, and to manage… (more)

Subjects/Keywords: Power distribution; Power system modeling; Parameter estimation; Power system measurements; Power system simulation; Regression analysis; Smart grids

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APA (6th Edition):

Peppanen, J. A. (2016). Improving distribution system model accuracy by leveraging ubiquitous sensors. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58179

Chicago Manual of Style (16th Edition):

Peppanen, Jouni Aleksi. “Improving distribution system model accuracy by leveraging ubiquitous sensors.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/58179.

MLA Handbook (7th Edition):

Peppanen, Jouni Aleksi. “Improving distribution system model accuracy by leveraging ubiquitous sensors.” 2016. Web. 18 Oct 2019.

Vancouver:

Peppanen JA. Improving distribution system model accuracy by leveraging ubiquitous sensors. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/58179.

Council of Science Editors:

Peppanen JA. Improving distribution system model accuracy by leveraging ubiquitous sensors. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/58179


Georgia Tech

4. Zhang, Chengliang. Robust optimization with applications in maritime inventory routing.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 In recent years, the importance of incorporating uncertainty into planning models for logistics and transportation systems has been widely recognized in the Operations Research and… (more)

Subjects/Keywords: Robust planning; Inventory routing; Maritime transportation; Mixed integer programming

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APA (6th Edition):

Zhang, C. (2015). Robust optimization with applications in maritime inventory routing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54863

Chicago Manual of Style (16th Edition):

Zhang, Chengliang. “Robust optimization with applications in maritime inventory routing.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/54863.

MLA Handbook (7th Edition):

Zhang, Chengliang. “Robust optimization with applications in maritime inventory routing.” 2015. Web. 18 Oct 2019.

Vancouver:

Zhang C. Robust optimization with applications in maritime inventory routing. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/54863.

Council of Science Editors:

Zhang C. Robust optimization with applications in maritime inventory routing. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54863


Georgia Tech

5. Hu, Liujia. Convergent algorithms in simulation optimization.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 It is frequently the case that deterministic optimization models could be made more practical by explicitly incorporating uncertainty. The resulting stochastic optimization problems are in… (more)

Subjects/Keywords: Simulation optimization; Adaptive random search; Global convergence; Stochastic constraints

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APA (6th Edition):

Hu, L. (2015). Convergent algorithms in simulation optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54883

Chicago Manual of Style (16th Edition):

Hu, Liujia. “Convergent algorithms in simulation optimization.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/54883.

MLA Handbook (7th Edition):

Hu, Liujia. “Convergent algorithms in simulation optimization.” 2015. Web. 18 Oct 2019.

Vancouver:

Hu L. Convergent algorithms in simulation optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/54883.

Council of Science Editors:

Hu L. Convergent algorithms in simulation optimization. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54883


Georgia Tech

6. Costley, Mitcham Hudson. Prosumer-based decentralized unit commitment for future electricity grids.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 The contributions of this research are a scalable formulation and solution method for decentralized unit commitment, experimental results comparing decentralized unit commitment solution times to… (more)

Subjects/Keywords: Power systems; Unit commitment; Optimization

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APA (6th Edition):

Costley, M. H. (2015). Prosumer-based decentralized unit commitment for future electricity grids. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54890

Chicago Manual of Style (16th Edition):

Costley, Mitcham Hudson. “Prosumer-based decentralized unit commitment for future electricity grids.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/54890.

MLA Handbook (7th Edition):

Costley, Mitcham Hudson. “Prosumer-based decentralized unit commitment for future electricity grids.” 2015. Web. 18 Oct 2019.

Vancouver:

Costley MH. Prosumer-based decentralized unit commitment for future electricity grids. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/54890.

Council of Science Editors:

Costley MH. Prosumer-based decentralized unit commitment for future electricity grids. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54890


Georgia Tech

7. Ozlu, Ahmet Oguzhan. Optimization approaches for designing baseball scout networks under uncertainty.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Major League Baseball (MLB) is a 30-team North American professional baseball league and Minor League Baseball (MiLB) is the hierarchy of developmental professional baseball teams… (more)

Subjects/Keywords: OR in sports; Scheduling; Integer programming; Heuristics; Schedule recovery; Discrete event simulation; Simulation and optimization

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APA (6th Edition):

Ozlu, A. O. (2016). Optimization approaches for designing baseball scout networks under uncertainty. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54983

Chicago Manual of Style (16th Edition):

Ozlu, Ahmet Oguzhan. “Optimization approaches for designing baseball scout networks under uncertainty.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/54983.

MLA Handbook (7th Edition):

Ozlu, Ahmet Oguzhan. “Optimization approaches for designing baseball scout networks under uncertainty.” 2016. Web. 18 Oct 2019.

Vancouver:

Ozlu AO. Optimization approaches for designing baseball scout networks under uncertainty. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/54983.

Council of Science Editors:

Ozlu AO. Optimization approaches for designing baseball scout networks under uncertainty. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/54983


Georgia Tech

8. Angulo Olivares, Gustavo, I. Integer programming approaches for semicontinuous and stochastic optimization.

Degree: PhD, Industrial and Systems Engineering, 2014, Georgia Tech

 This thesis concerns the application of mixed-integer programming techniques to solve special classes of network flow problems and stochastic integer programs. We draw tools from… (more)

Subjects/Keywords: Integer programming; Stochastic programming; Forbidden vertices; Mathematical optimization; Dynamic programming; Integer programming

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APA (6th Edition):

Angulo Olivares, Gustavo, I. (2014). Integer programming approaches for semicontinuous and stochastic optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51862

Chicago Manual of Style (16th Edition):

Angulo Olivares, Gustavo, I. “Integer programming approaches for semicontinuous and stochastic optimization.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/51862.

MLA Handbook (7th Edition):

Angulo Olivares, Gustavo, I. “Integer programming approaches for semicontinuous and stochastic optimization.” 2014. Web. 18 Oct 2019.

Vancouver:

Angulo Olivares, Gustavo I. Integer programming approaches for semicontinuous and stochastic optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/51862.

Council of Science Editors:

Angulo Olivares, Gustavo I. Integer programming approaches for semicontinuous and stochastic optimization. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/51862


Georgia Tech

9. Xin, Linwei. New approaches to inventory control: algorithms, asymptotics and robustness.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 The fundamental problem of managing an inventory over time in the presence of stochastic demand is one of the core problems of operations research. This… (more)

Subjects/Keywords: Inventory control

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APA (6th Edition):

Xin, L. (2015). New approaches to inventory control: algorithms, asymptotics and robustness. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53852

Chicago Manual of Style (16th Edition):

Xin, Linwei. “New approaches to inventory control: algorithms, asymptotics and robustness.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/53852.

MLA Handbook (7th Edition):

Xin, Linwei. “New approaches to inventory control: algorithms, asymptotics and robustness.” 2015. Web. 18 Oct 2019.

Vancouver:

Xin L. New approaches to inventory control: algorithms, asymptotics and robustness. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/53852.

Council of Science Editors:

Xin L. New approaches to inventory control: algorithms, asymptotics and robustness. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53852


Georgia Tech

10. Alquthami, Thamer. A smart house energy management system.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 The impact of distributed energy resources (DERs), electric vehicles/plug-in hybrid electric vehicles (EVs/PHEVs), and smart appliances on the distribution grid has been expected to be… (more)

Subjects/Keywords: Smart grid; Energy management; House energy management; Energy optimization

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APA (6th Edition):

Alquthami, T. (2015). A smart house energy management system. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53900

Chicago Manual of Style (16th Edition):

Alquthami, Thamer. “A smart house energy management system.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/53900.

MLA Handbook (7th Edition):

Alquthami, Thamer. “A smart house energy management system.” 2015. Web. 18 Oct 2019.

Vancouver:

Alquthami T. A smart house energy management system. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/53900.

Council of Science Editors:

Alquthami T. A smart house energy management system. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53900


Georgia Tech

11. Megahed, Aly. Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts.

Degree: PhD, Industrial and Systems Engineering, 2014, Georgia Tech

 In this thesis, we study three supply chain planning problems. The first two problems fall in the tactical planning level, while the third one falls… (more)

Subjects/Keywords: Wind turbines; Supply chain management; Tactical planning; Backorder penalties; Inventory; Supply chain planning; Supplier uncertainty/unreliability; Stochastic programming; Bill of materials; Planning under uncertainty; Lot sizing; Quantity discounts; Local search; Mixed integer programming; Variable neighborhood descent; Supplier selection; Integer programming-based search; Production/distribution

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APA (6th Edition):

Megahed, A. (2014). Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54011

Chicago Manual of Style (16th Edition):

Megahed, Aly. “Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/54011.

MLA Handbook (7th Edition):

Megahed, Aly. “Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts.” 2014. Web. 18 Oct 2019.

Vancouver:

Megahed A. Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/54011.

Council of Science Editors:

Megahed A. Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54011


Georgia Tech

12. Lee, Junho. Track layout accommodating dynamic routing in automated material handling systems.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Modern semiconductor fabrication facilities depend on automated material handling systems (AMHSs) to manage the processes and variations in time required to produce advanced semiconductor products.… (more)

Subjects/Keywords: Semiconductor manufacturing; Automated material handling systems; Network design problems; Dynamic routing; Alternative paths

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APA (6th Edition):

Lee, J. (2016). Track layout accommodating dynamic routing in automated material handling systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55562

Chicago Manual of Style (16th Edition):

Lee, Junho. “Track layout accommodating dynamic routing in automated material handling systems.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/55562.

MLA Handbook (7th Edition):

Lee, Junho. “Track layout accommodating dynamic routing in automated material handling systems.” 2016. Web. 18 Oct 2019.

Vancouver:

Lee J. Track layout accommodating dynamic routing in automated material handling systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/55562.

Council of Science Editors:

Lee J. Track layout accommodating dynamic routing in automated material handling systems. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55562


Georgia Tech

13. Kocuk, Burak. Global optimization methods for optimal power flow and transmission switching problems in electric power systems.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Power engineering is concerned with the generation, transmission, and distribution of electricity over electric power network, which is arguably one of the largest engineering systems… (more)

Subjects/Keywords: Global optimization; Conic programming; Mixed-integer nonlinear programming; Power systems; Optimal power flow; Transmission switching

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APA (6th Edition):

Kocuk, B. (2016). Global optimization methods for optimal power flow and transmission switching problems in electric power systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55633

Chicago Manual of Style (16th Edition):

Kocuk, Burak. “Global optimization methods for optimal power flow and transmission switching problems in electric power systems.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/55633.

MLA Handbook (7th Edition):

Kocuk, Burak. “Global optimization methods for optimal power flow and transmission switching problems in electric power systems.” 2016. Web. 18 Oct 2019.

Vancouver:

Kocuk B. Global optimization methods for optimal power flow and transmission switching problems in electric power systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/55633.

Council of Science Editors:

Kocuk B. Global optimization methods for optimal power flow and transmission switching problems in electric power systems. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55633


Georgia Tech

14. Lorca Galvez, Alvaro Hugo. Robust optimization for renewable energy integration in power system operations.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Optimization provides critical support for the operation of electric power systems. As power systems evolve, enhanced operational methodologies are required, and innovative optimization models have… (more)

Subjects/Keywords: Robust optimization; Power system operations; Renewable energy

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APA (6th Edition):

Lorca Galvez, A. H. (2016). Robust optimization for renewable energy integration in power system operations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55653

Chicago Manual of Style (16th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/55653.

MLA Handbook (7th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Web. 18 Oct 2019.

Vancouver:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/55653.

Council of Science Editors:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55653


Georgia Tech

15. Na, Byungsoo. Optimization of automated float glass lines.

Degree: PhD, Industrial and Systems Engineering, 2010, Georgia Tech

 Motivated by operational issues in real-world glass manufacturing, this thesis addresses a problem of laying out and sequencing the orders so as to minimize wasted… (more)

Subjects/Keywords: Optimization; Cyclic schedule; Cutting; Scheduling; Float line; Glass; Heuristics; Heuristic algorithms; Programming (Mathematics); Production scheduling

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APA (6th Edition):

Na, B. (2010). Optimization of automated float glass lines. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/39637

Chicago Manual of Style (16th Edition):

Na, Byungsoo. “Optimization of automated float glass lines.” 2010. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/39637.

MLA Handbook (7th Edition):

Na, Byungsoo. “Optimization of automated float glass lines.” 2010. Web. 18 Oct 2019.

Vancouver:

Na B. Optimization of automated float glass lines. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/39637.

Council of Science Editors:

Na B. Optimization of automated float glass lines. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/39637


Georgia Tech

16. Vielma Centeno, Juan Pablo. Mixed integer programming approaches for nonlinear and stochastic programming.

Degree: PhD, Industrial and Systems Engineering, 2009, Georgia Tech

 In this thesis we study how to solve some nonconvex optimization problems by using methods that capitalize on the success of Linear Programming (LP) based… (more)

Subjects/Keywords: Mixed integer programming; Stochastic programming; Mathematical optimization; Nonconvex programming

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APA (6th Edition):

Vielma Centeno, J. P. (2009). Mixed integer programming approaches for nonlinear and stochastic programming. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29624

Chicago Manual of Style (16th Edition):

Vielma Centeno, Juan Pablo. “Mixed integer programming approaches for nonlinear and stochastic programming.” 2009. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/29624.

MLA Handbook (7th Edition):

Vielma Centeno, Juan Pablo. “Mixed integer programming approaches for nonlinear and stochastic programming.” 2009. Web. 18 Oct 2019.

Vancouver:

Vielma Centeno JP. Mixed integer programming approaches for nonlinear and stochastic programming. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/29624.

Council of Science Editors:

Vielma Centeno JP. Mixed integer programming approaches for nonlinear and stochastic programming. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29624


Georgia Tech

17. Ye, Fan. Information relaxation in stochastic optimal control.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 Dynamic programming is a principal method for analyzing stochastic optimal control problems. However, the exact computation of dynamic programming can be intractable in large-scale problems… (more)

Subjects/Keywords: Dynamic programming; Stochastic control; Information relaxation; Duality

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APA (6th Edition):

Ye, F. (2015). Information relaxation in stochastic optimal control. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55511

Chicago Manual of Style (16th Edition):

Ye, Fan. “Information relaxation in stochastic optimal control.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/55511.

MLA Handbook (7th Edition):

Ye, Fan. “Information relaxation in stochastic optimal control.” 2015. Web. 18 Oct 2019.

Vancouver:

Ye F. Information relaxation in stochastic optimal control. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/55511.

Council of Science Editors:

Ye F. Information relaxation in stochastic optimal control. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55511


Georgia Tech

18. Feizollahi, Mohammadjavad. Large-scale unit commitment: Decentralized mixed integer programming approaches.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 We investigate theory and application of decentralized optimization for mixed integer programming (MIP) problems. Our focus is on loosely coupled MIPs where different blocks of… (more)

Subjects/Keywords: Decentralized optimization; Augmented Lagrangian; Unit commitment; Mixed integer programming

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APA (6th Edition):

Feizollahi, M. (2015). Large-scale unit commitment: Decentralized mixed integer programming approaches. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56169

Chicago Manual of Style (16th Edition):

Feizollahi, Mohammadjavad. “Large-scale unit commitment: Decentralized mixed integer programming approaches.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/56169.

MLA Handbook (7th Edition):

Feizollahi, Mohammadjavad. “Large-scale unit commitment: Decentralized mixed integer programming approaches.” 2015. Web. 18 Oct 2019.

Vancouver:

Feizollahi M. Large-scale unit commitment: Decentralized mixed integer programming approaches. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/56169.

Council of Science Editors:

Feizollahi M. Large-scale unit commitment: Decentralized mixed integer programming approaches. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/56169


Georgia Tech

19. Yildirim, Murat. Predictive analytics and optimization for improved electric power network reliability and operation.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Advances in sensor technology, data storage and signal processing enable methods to indirectly monitor many complex engineering systems. The aim of this dissertation is to… (more)

Subjects/Keywords: Asset reliability and sustainability; Condition based maintenance; Generation maintenance scheduling; Sensor-driven prognosis

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APA (6th Edition):

Yildirim, M. (2016). Predictive analytics and optimization for improved electric power network reliability and operation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60106

Chicago Manual of Style (16th Edition):

Yildirim, Murat. “Predictive analytics and optimization for improved electric power network reliability and operation.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/60106.

MLA Handbook (7th Edition):

Yildirim, Murat. “Predictive analytics and optimization for improved electric power network reliability and operation.” 2016. Web. 18 Oct 2019.

Vancouver:

Yildirim M. Predictive analytics and optimization for improved electric power network reliability and operation. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/60106.

Council of Science Editors:

Yildirim M. Predictive analytics and optimization for improved electric power network reliability and operation. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/60106


Georgia Tech

20. Munguia Conejero, Lluis-Miquel M. High performance computing algorithms for discrete optimization.

Degree: PhD, Computational Science and Engineering, 2017, Georgia Tech

 This thesis concerns the application of High Performance Computing to Discrete Optimization, and the development of massively parallel algorithms designed to accelerate the solving process… (more)

Subjects/Keywords: Integer programming; Discrete optimization; Parallel computing; Primal heuristics; High performance computing

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APA (6th Edition):

Munguia Conejero, L. M. (2017). High performance computing algorithms for discrete optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60689

Chicago Manual of Style (16th Edition):

Munguia Conejero, Lluis-Miquel M. “High performance computing algorithms for discrete optimization.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/60689.

MLA Handbook (7th Edition):

Munguia Conejero, Lluis-Miquel M. “High performance computing algorithms for discrete optimization.” 2017. Web. 18 Oct 2019.

Vancouver:

Munguia Conejero LM. High performance computing algorithms for discrete optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/60689.

Council of Science Editors:

Munguia Conejero LM. High performance computing algorithms for discrete optimization. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60689


Georgia Tech

21. Karabulut, Ezgi. Distributed integer programming.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

 In this thesis, we study distributed integer programming problems that involve multiple players with integer programming problems linked together with a common resource constraint. Our… (more)

Subjects/Keywords: Decentralized optimization; Resource allocation; Concavity; Online optimization

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APA (6th Edition):

Karabulut, E. (2017). Distributed integer programming. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59194

Chicago Manual of Style (16th Edition):

Karabulut, Ezgi. “Distributed integer programming.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/59194.

MLA Handbook (7th Edition):

Karabulut, Ezgi. “Distributed integer programming.” 2017. Web. 18 Oct 2019.

Vancouver:

Karabulut E. Distributed integer programming. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/59194.

Council of Science Editors:

Karabulut E. Distributed integer programming. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59194


Georgia Tech

22. Daugherty, Stephen G. Multi-agent routing in shared guidepath networks.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

 Motivated by a broad spectrum of applications ranging from automated zone-controlled, unit-load material handling systems to the movement of ions within a quantum computer, this… (more)

Subjects/Keywords: Logistics; Routing; Multi-robot path planning

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APA (6th Edition):

Daugherty, S. G. (2017). Multi-agent routing in shared guidepath networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59196

Chicago Manual of Style (16th Edition):

Daugherty, Stephen G. “Multi-agent routing in shared guidepath networks.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/59196.

MLA Handbook (7th Edition):

Daugherty, Stephen G. “Multi-agent routing in shared guidepath networks.” 2017. Web. 18 Oct 2019.

Vancouver:

Daugherty SG. Multi-agent routing in shared guidepath networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/59196.

Council of Science Editors:

Daugherty SG. Multi-agent routing in shared guidepath networks. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59196


Georgia Tech

23. Gao, Rui. Distributionally robust stochastic optimization with applications in statistical learning.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

 In this thesis, we study distributionally robust stochastic optimization (DRSO), a recent emerging framework for solving decision-making under uncertainty. In this framework, instead of assuming… (more)

Subjects/Keywords: Distributionally robust optimization; Wasserstein distance; Optimal transport; Regularization; Copula

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APA (6th Edition):

Gao, R. (2018). Distributionally robust stochastic optimization with applications in statistical learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59834

Chicago Manual of Style (16th Edition):

Gao, Rui. “Distributionally robust stochastic optimization with applications in statistical learning.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/59834.

MLA Handbook (7th Edition):

Gao, Rui. “Distributionally robust stochastic optimization with applications in statistical learning.” 2018. Web. 18 Oct 2019.

Vancouver:

Gao R. Distributionally robust stochastic optimization with applications in statistical learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/59834.

Council of Science Editors:

Gao R. Distributionally robust stochastic optimization with applications in statistical learning. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59834


Georgia Tech

24. Blado, Daniel E. Relaxations for the dynamic knapsack problem with stochastic item sizes.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

 We consider a version of the knapsack problem in which an item size is random and revealed only when the decision maker attempts to insert… (more)

Subjects/Keywords: Optimization; Stochastic knapsack; Optimal policy; Dynamic programming; Bound/policy gap

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APA (6th Edition):

Blado, D. E. (2018). Relaxations for the dynamic knapsack problem with stochastic item sizes. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60199

Chicago Manual of Style (16th Edition):

Blado, Daniel E. “Relaxations for the dynamic knapsack problem with stochastic item sizes.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/60199.

MLA Handbook (7th Edition):

Blado, Daniel E. “Relaxations for the dynamic knapsack problem with stochastic item sizes.” 2018. Web. 18 Oct 2019.

Vancouver:

Blado DE. Relaxations for the dynamic knapsack problem with stochastic item sizes. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/60199.

Council of Science Editors:

Blado DE. Relaxations for the dynamic knapsack problem with stochastic item sizes. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60199


Georgia Tech

25. Deboever, Jeremiah. Fast Interconnection Analysis of PV Systems Using Vector Quantization.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 The objective of the proposed research is to develop fast interconnection analysis to assess solar photovoltaic (PV) system impacts on distribution networks. As emerging technologies,… (more)

Subjects/Keywords: PV systems; Electric Distribution Networks

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APA (6th Edition):

Deboever, J. (2018). Fast Interconnection Analysis of PV Systems Using Vector Quantization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61137

Chicago Manual of Style (16th Edition):

Deboever, Jeremiah. “Fast Interconnection Analysis of PV Systems Using Vector Quantization.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/61137.

MLA Handbook (7th Edition):

Deboever, Jeremiah. “Fast Interconnection Analysis of PV Systems Using Vector Quantization.” 2018. Web. 18 Oct 2019.

Vancouver:

Deboever J. Fast Interconnection Analysis of PV Systems Using Vector Quantization. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/61137.

Council of Science Editors:

Deboever J. Fast Interconnection Analysis of PV Systems Using Vector Quantization. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61137


Georgia Tech

26. Torrico Palacios, Alfredo Ignacio. RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION.

Degree: PhD, Industrial and Systems Engineering, 2019, Georgia Tech

 Resource allocation and subset selection are two relevant classes of problems in the core of combinatorial optimization. Over the past decade, there has been an… (more)

Subjects/Keywords: Combinatorial Optimization; Online Optimization; Online Bipartite Matching; Constrained Submodular Maximization

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APA (6th Edition):

Torrico Palacios, A. I. (2019). RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61720

Chicago Manual of Style (16th Edition):

Torrico Palacios, Alfredo Ignacio. “RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/61720.

MLA Handbook (7th Edition):

Torrico Palacios, Alfredo Ignacio. “RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION.” 2019. Web. 18 Oct 2019.

Vancouver:

Torrico Palacios AI. RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/61720.

Council of Science Editors:

Torrico Palacios AI. RESOURCE ALLOCATION AND SUBSET SELECTION: NEW APPROACHES AT THE INTERFACE BETWEEN DISCRETE AND CONTINUOUS OPTIMIZATION. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61720


Georgia Tech

27. Basciftci, Beste. Data-driven stochastic optimization approaches with applications in power systems.

Degree: PhD, Industrial and Systems Engineering, 2019, Georgia Tech

 In this thesis, we focus on data-driven stochastic optimization problems with an emphasis in power systems applications. On the one hand, we address the inefficiencies… (more)

Subjects/Keywords: Optimization under uncertainty; Energy systems

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APA (6th Edition):

Basciftci, B. (2019). Data-driven stochastic optimization approaches with applications in power systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61765

Chicago Manual of Style (16th Edition):

Basciftci, Beste. “Data-driven stochastic optimization approaches with applications in power systems.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/61765.

MLA Handbook (7th Edition):

Basciftci, Beste. “Data-driven stochastic optimization approaches with applications in power systems.” 2019. Web. 18 Oct 2019.

Vancouver:

Basciftci B. Data-driven stochastic optimization approaches with applications in power systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/61765.

Council of Science Editors:

Basciftci B. Data-driven stochastic optimization approaches with applications in power systems. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61765


Georgia Tech

28. Sandoval Zapata, Marcelo Francisco. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Adoption of distributed energy resources (DERs) such as solar photovoltaic generators, energy storage, demand response devices, energy efficiency and electric vehicles is expected to grow… (more)

Subjects/Keywords: Distributed energy resources; Power systems economics; Integrated grid planning; Risk-averse two-stage stochastic optimization; Power system architecture; Locational value analysis

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APA (6th Edition):

Sandoval Zapata, M. F. (2018). Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59887

Chicago Manual of Style (16th Edition):

Sandoval Zapata, Marcelo Francisco. “Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/59887.

MLA Handbook (7th Edition):

Sandoval Zapata, Marcelo Francisco. “Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.” 2018. Web. 18 Oct 2019.

Vancouver:

Sandoval Zapata MF. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/59887.

Council of Science Editors:

Sandoval Zapata MF. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59887

29. Wang, Qianyi. Theory and computation of sparse cutting planes.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

 Cutting plane plays an important role in the theory and computation of integer programming. Nowadays, most state-of-the-art integer programming solvers tend to bias their cutting… (more)

Subjects/Keywords: Integer programming; Cutting plane; Sparse; Algorithm; Theory

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APA (6th Edition):

Wang, Q. (2016). Theory and computation of sparse cutting planes. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56307

Chicago Manual of Style (16th Edition):

Wang, Qianyi. “Theory and computation of sparse cutting planes.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/56307.

MLA Handbook (7th Edition):

Wang, Qianyi. “Theory and computation of sparse cutting planes.” 2016. Web. 18 Oct 2019.

Vancouver:

Wang Q. Theory and computation of sparse cutting planes. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/56307.

Council of Science Editors:

Wang Q. Theory and computation of sparse cutting planes. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56307

30. Guzman Paredes, Cristobal. Information, complexity and structure in convex optimization.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

 This thesis is focused on the limits of performance of large-scale convex optimization algorithms. Classical theory of oracle complexity, first proposed by Nemirovski and Yudin… (more)

Subjects/Keywords: Convex optimization; Optimization algorithms; Complexity theory; Lower bounds

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APA (6th Edition):

Guzman Paredes, C. (2015). Information, complexity and structure in convex optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53577

Chicago Manual of Style (16th Edition):

Guzman Paredes, Cristobal. “Information, complexity and structure in convex optimization.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 18, 2019. http://hdl.handle.net/1853/53577.

MLA Handbook (7th Edition):

Guzman Paredes, Cristobal. “Information, complexity and structure in convex optimization.” 2015. Web. 18 Oct 2019.

Vancouver:

Guzman Paredes C. Information, complexity and structure in convex optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 18]. Available from: http://hdl.handle.net/1853/53577.

Council of Science Editors:

Guzman Paredes C. Information, complexity and structure in convex optimization. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53577

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