Approaches for multi-objective combinatorial optimization problems

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2007
Lokman, Banu
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In this thesis, we develop two exact algorithms and a heuristic procedure for Multiobjective Combinatorial Optimization Problems (MOCO). Our exact algorithms guarantee to generate all nondominated solutions of any MOCO problem. We test the performance of the algorithms on randomly generated problems including the Multiobjective Knapsack Problem, Multi-objective Shortest Path Problem and Multi-objective Spanning Tree Problem. Although we showed the algorithms work much better than the previous ones, we also proposed a fast heuristic method to approximate efficient frontier since it will also be applicable for real-sized problems. Our heuristic approach is based on fitting a surface to approximate the efficient frontier. We experiment our heuristic on randomly generated problems to test how well the heuristic procedure approximates the efficient frontier. Our results showed the heuristic method works well.
Engineering Mathematics., Engineering Analysis.
http://etd.lib.metu.edu.tr/upload/12608443/index.pdf
https://hdl.handle.net/11511/16905
Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats
B. Lokman, “Approaches for multi-objective combinatorial optimization problems,” M.S. - Master of Science, Middle East Technical University, 2007.
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