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dc.contributor.authorKiran Kumar, M S N-
dc.contributor.authorBiswal, B B-
dc.contributor.authorMahapatra, S S-
dc.contributor.authorJena, N-
dc.identifier.citationModeling and Simulation Coimbatore, 27-29 August 2007en
dc.descriptionCopyright for the paper belongs to Proceedings Publisheren
dc.description.abstractThe concept of global work-place in the recent past has been the major driving factor to remain competitive by using the appropriate techniques in various aspects of manufacturing activities. Genetic Algorithm (GA) has proven to be a useful method of optimization for the combinatorial optimization problems. Particle Swarm Optimization (PSO), a new method of optimization, is able to accomplish the same goal as GA optimization in a faster way. The purpose of the present work is to investigate performance of the two algorithms when applied to flowshop scheduling with fuzzy due dates. An attempt has been made to hybridize the two algorithms in series. It is established that the hybrid algorithm (PSOGA) produces better results on problems of larger size when compared to the individual performance of the algorithms.en
dc.format.extent93228 bytes-
dc.publisherProceedings of the International Conference onen
dc.subjectflow shop schedulingen
dc.subjectFuzzy Due Datesen
dc.subjectParticle swarm optimizationen
dc.subjectProduction Schedulingen
dc.titleOptimization of Flowshop Scheduling with Fuzzy Due Dates Using a Hybrid Evolutionary Algorithmen
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