Multiobjective Prototype Optimization with Evolved Improvement Steps

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Multiobjective Prototype Optimization with Evolved Improvement Steps
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.
Jirí Kubalík, Richard Mordinyi, Stef
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where EVOW
Authors Jirí Kubalík, Richard Mordinyi, Stefan Biffl
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