Multi-Objective Simulation-Based Optimization of Production Systems with Consideration Noise
2008 (English)In: / [ed] Bengt Åke Lindberg & Johan Stahre, Stockholm: Swedish Production Academy , 2008Conference paper (Refereed)
Many production optimization problems approached by simulation are subject to noise.When evolutionary algorithms are applied to such problems, noise during evaluation of solutions adversely affects the evolutionary selection process and the performance of the algorithm. In this paper we present a noise compensation technique that efficiently deals with the negative effects of noisy simulations in multi-objective optimization problems. Basically, this technique uses an iterative re-sampling procedure that reduces the noise until the likelihood of selecting the correct solution reaches a given confidence level. The technique is implemented in MOPSA-EA, an existing evolutionary algorithm designed specifically for real-world simulation-optimization problems. In evaluating the new technique, it is applied on a benchmark problem and on two real-world problems of manufacturing optimization. A comparison of the performance of existing algorithms indicates the potential of the proposed technique.
Place, publisher, year, edition, pages
Stockholm: Swedish Production Academy , 2008.
simulation, optimization, noise
IdentifiersURN: urn:nbn:se:his:diva-7181OAI: oai:DiVA.org:his-7181DiVA: diva2:604203
2nd Swedish Production Symposium (SPS) 2008, Stockholm, Sweden, November 18-20, 2008