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You searched for `+publisher:"Georgia Tech" +contributor:("Dey, Santanu S.")`

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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

URL: http://hdl.handle.net/1853/58274

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

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/55633

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

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/58678

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

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/53517

► 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…
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Subjects/Keywords: Submodular optimization; Mixed-integer optimization

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/52309

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

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/50237

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

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1853/47567

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

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

MLA Handbook (7^{th} 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