Talks and Poster Presentations (with Proceedings-Entry):
J. Kubalik, R. Mordinyi, S. Biffl:
"Multiobjective Prototype Optimization with Evolved Improvement Steps";
Talk: 8th European Conference, EvoCOP 2008,
- 2008-03-28; in: "Evolutionary Computation in Combinatorial Optimization",
Recently, a new iterative optimization framework utilizing an evolutionary algorithm called "Prototype Optimization with Evolved iMprovement Steps" (POEMS) was introduced, which showed good performance on hard optimization problems - large instances of TSP and real-valued optimization problems. Especially, on discrete optimization problems such as the TSP the algorithm exhibited much better search capabilities than the standard evolutionary approaches. In many real-world optimization problems a solution is sought for multiple (conflicting) optimization criteria. This paper proposes a multiobjective version of the POEMS algorithm (mPOEMS), which was experimentally evaluated on the multiobjective 0/1 knapsack problem with alternative multiobjective evolutionary algorithms. Major result of the experiments was that the proposed algorithm performed comparable to or better than the alternative algorithms.
multiobjective optimization - evolutionary algorithms - multiobjective 0/1 knapsack problem
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.