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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/691

Title: Optimization of Flowshop Scheduling with Fuzzy Due Dates Using a Hybrid Evolutionary Algorithm
Authors: Kiran Kumar, M S N
Biswal, B B
Mahapatra, S S
Jena, N
Keywords: Heruistics
flow shop scheduling
Fuzzy Due Dates
Metaheuristics
Particle swarm optimization
Production Scheduling
Issue Date: 2007
Publisher: Proceedings of the International Conference on
Citation: Modeling and Simulation Coimbatore, 27-29 August 2007
Abstract: The 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.
Description: Copyright for the paper belongs to Proceedings Publisher
URI: http://hdl.handle.net/2080/691
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