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You searched for +publisher:"Georgia Tech" +contributor:("Dey, Santanu S."). Showing records 1 – 7 of 7 total matches.

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1. Zink, Daniel. A reduction framework for approximate extended formulations and a faster algorithm for convex optimization.

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

 Linear programming (LP) and semidefinite programming (SDP) are among the most important tools in Operations Research and Computer Science. In this work we study the… (more)

Subjects/Keywords: Extended formulations; Linear programming; Semidefinite programming; Approximations; Convex optimization; Frank-Wolfe method; Conditional gradients

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APA (6th Edition):

Zink, D. (2017). A reduction framework for approximate extended formulations and a faster algorithm for convex optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58274

Chicago Manual of Style (16th Edition):

Zink, Daniel. “A reduction framework for approximate extended formulations and a faster algorithm for convex optimization.” 2017. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/58274.

MLA Handbook (7th Edition):

Zink, Daniel. “A reduction framework for approximate extended formulations and a faster algorithm for convex optimization.” 2017. Web. 12 Dec 2019.

Vancouver:

Zink D. A reduction framework for approximate extended formulations and a faster algorithm for convex optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/58274.

Council of Science Editors:

Zink D. A reduction framework for approximate extended formulations and a faster algorithm for convex optimization. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58274


Georgia Tech

2. 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 December 12, 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. 12 Dec 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 Dec 12]. 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

3. Xie, Weijun. Relaxations and approximations of chance constrained stochastic programs.

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

 A chance constrained stochastic programming (CCSP) problem involves constraints with random parameters that are required to be satisfied with a prespecified probability threshold. Such constraints… (more)

Subjects/Keywords: chance constraint; approximation algorithm; Lagrangian relaxation; distributionally robust; convex program

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APA (6th Edition):

Xie, W. (2017). Relaxations and approximations of chance constrained stochastic programs. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58678

Chicago Manual of Style (16th Edition):

Xie, Weijun. “Relaxations and approximations of chance constrained stochastic programs.” 2017. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/58678.

MLA Handbook (7th Edition):

Xie, Weijun. “Relaxations and approximations of chance constrained stochastic programs.” 2017. Web. 12 Dec 2019.

Vancouver:

Xie W. Relaxations and approximations of chance constrained stochastic programs. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/58678.

Council of Science Editors:

Xie W. Relaxations and approximations of chance constrained stochastic programs. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58678

4. Yu, Jiajin. Optimization and separation for structured submodular functions with constraints.

Degree: PhD, Computer Science, 2015, Georgia Tech

 Various kinds of optimization problems involve nonlinear functions of binary variables that exhibit a property of diminishing marginal returns. Such a property is known as… (more)

Subjects/Keywords: Submodular optimization; Mixed-integer optimization

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APA (6th Edition):

Yu, J. (2015). Optimization and separation for structured submodular functions with constraints. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53517

Chicago Manual of Style (16th Edition):

Yu, Jiajin. “Optimization and separation for structured submodular functions with constraints.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/53517.

MLA Handbook (7th Edition):

Yu, Jiajin. “Optimization and separation for structured submodular functions with constraints.” 2015. Web. 12 Dec 2019.

Vancouver:

Yu J. Optimization and separation for structured submodular functions with constraints. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/53517.

Council of Science Editors:

Yu J. Optimization and separation for structured submodular functions with constraints. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53517

5. Moran Ramirez, Diego Alejandro. Fundamental properties of convex mixed-integer programs.

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

 In this Ph.D. dissertation research, we lay the mathematical foundations of various fundamental concepts in convex mixed-integer programs (MIPs), that is, optimization problems where all… (more)

Subjects/Keywords: Integer programming; Cutting planes; Convex hull; Integer hull; Optimization; Split cuts

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APA (6th Edition):

Moran Ramirez, D. A. (2014). Fundamental properties of convex mixed-integer programs. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52309

Chicago Manual of Style (16th Edition):

Moran Ramirez, Diego Alejandro. “Fundamental properties of convex mixed-integer programs.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/52309.

MLA Handbook (7th Edition):

Moran Ramirez, Diego Alejandro. “Fundamental properties of convex mixed-integer programs.” 2014. Web. 12 Dec 2019.

Vancouver:

Moran Ramirez DA. Fundamental properties of convex mixed-integer programs. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/52309.

Council of Science Editors:

Moran Ramirez DA. Fundamental properties of convex mixed-integer programs. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52309

6. He, Qie. Topics in discrete optimization: models, complexity and algorithms.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

 In this dissertation we examine several discrete optimization problems through the perspectives of modeling, complexity and algorithms. We first provide a probabilistic comparison of split… (more)

Subjects/Keywords: Integer programming; Combinatorial optimization; Stochastic programming; Network flow; Production planning; Computational complexity; Mathematical optimization; Integer programming

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APA (6th Edition):

He, Q. (2013). Topics in discrete optimization: models, complexity and algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50237

Chicago Manual of Style (16th Edition):

He, Qie. “Topics in discrete optimization: models, complexity and algorithms.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/50237.

MLA Handbook (7th Edition):

He, Qie. “Topics in discrete optimization: models, complexity and algorithms.” 2013. Web. 12 Dec 2019.

Vancouver:

He Q. Topics in discrete optimization: models, complexity and algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/50237.

Council of Science Editors:

He Q. Topics in discrete optimization: models, complexity and algorithms. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50237

7. Qiu, Feng. Probabilistic covering problems.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

 This dissertation studies optimization problems that involve probabilistic covering constraints. A probabilistic constraint evaluates and requires that the probability that a set of constraints involving… (more)

Subjects/Keywords: Optimization; Stochastic programming; Chance-constrained program; Mixed-integer program; Probabilistic program; Covering problem; Mathematical optimization; Linear programming

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Qiu, F. (2013). Probabilistic covering problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47567

Chicago Manual of Style (16th Edition):

Qiu, Feng. “Probabilistic covering problems.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 12, 2019. http://hdl.handle.net/1853/47567.

MLA Handbook (7th Edition):

Qiu, Feng. “Probabilistic covering problems.” 2013. Web. 12 Dec 2019.

Vancouver:

Qiu F. Probabilistic covering problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Dec 12]. Available from: http://hdl.handle.net/1853/47567.

Council of Science Editors:

Qiu F. Probabilistic covering problems. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47567

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