M.S. (Master of Science)
Department of Mathematical Sciences
In this thesis we study and compare computational capability of two solvers, Gurobi and BiqCrunch, and their capabilities to solve various binary quadratic and linear programming problems. We review two types of programming models for three types of combinatorial optimization problems, namely Max-Cut, Max Independent Set, and Max-$k$-Cluster. We also review the Reformulation-Linearization Technique (RLT) and Semidefinite Programming (SDP) approaches for solving these models, go over the software and hardware used to solve these problems, and finally review the numerical results obtained by solving the problems.
Mackelfresh, William Cody, "A Computational Study of Binary Linear and Quadratic Programming and Solvers" (2020). Graduate Research Theses & Dissertations. 7389.
Northern Illinois University
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