Stefan Rocktäschel introduces a branch-and-bound algorithm that determines a cover of the efficient set of multiobjective mixed-integer convex optimization problems. He examines particular steps of this algorithm in detail and enhances the basic algorithm with additional modifications that ensure a more precise cover of the efficient set. Finally, he gives numerical results on some test instances.
Stefan Rocktäschel introduces a branch-and-bound algorithm that determines a cover of the efficient set of multiobjective mixed-integer convex optimization problems. He examines particular steps of this algorithm in detail and enhances the basic algorithm with additional modifications that ensure a more precise cover of the efficient set. Finally, he gives numerical results on some test instances.
Stefan Rocktäschel works as scientific assistant at the Institute for Mathematics of Technische Universität Ilmenau, Germany.
Inhaltsangabe
Theoretical basics for solving multiobjective mixed-integer convex optimization problems.- An algorithm for solving this class of optimization problems.- Test instances and numerical results.
Theoretical basics for solving multiobjective mixed-integer convex optimization problems.- An algorithm for solving this class of optimization problems.- Test instances and numerical results.
Theoretical basics for solving multiobjective mixed-integer convex optimization problems.- An algorithm for solving this class of optimization problems.- Test instances and numerical results.
Theoretical basics for solving multiobjective mixed-integer convex optimization problems.- An algorithm for solving this class of optimization problems.- Test instances and numerical results.
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