Identifying preferred solutions in multiobjective combinatorial optimization problems

Banu Lokman, Murat Koksalan

Research output: Contribution to journalArticlepeer-review

87 Downloads (Pure)


We develop an evolutionary algorithm for multi-objective combinatorial optimization problems. The algorithm aims at converging the preferred solutions of a decision maker. We test the performance of the algorithm on the multi-objective knapsack and multi-objective spanning tree problems. We generate the true nondominated solutions using an exact algorithm and compare the results with those of the evolutionary algorithm. We observe that the evolutionary algorithm works well in approximating the solutions in the preferred regions.
Original languageEnglish
Pages (from-to)1970-1981
JournalTurkish Journal of Electrical Engineering and Computer Sciences
Issue number3
Early online date2 May 2019
Publication statusPublished - 15 May 2019


Dive into the research topics of 'Identifying preferred solutions in multiobjective combinatorial optimization problems'. Together they form a unique fingerprint.

Cite this