An improved genetic-based particle swarm optimization for no-idle permutation flow shops with fuzzy processing time

Authors:
Qun Niu;Xingsheng Gu
Affiliations:
Research Institution of Automation, East China University of Science & Technology, Shanghai, China;Research Institution of Automation, East China University of Science & Technology, Shanghai, China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

Citing 5
Cited 0

Fuzzy flexible flow shops at two machine centers for continuous fuzzy domains

Information Sciences—Informatics and Computer Science: An International Journal
Real-time task sheduling with fuzzy deadlines and processing times

Fuzzy Sets and Systems
Scheduling under Fuzziness

Scheduling under Fuzziness
Particle swarm optimization for integer programming

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Jobshop scheduling with imprecise durations: a fuzzy approach

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Due to the uncertainty of the processing time in the practical production, no idle flow shop scheduling problem with fuzzy processing time is introduced. The objective is to find a sequence that minimizes the mean makespan and the spread of the makespan by using a method for ranking fuzzy numbers. The particle swarm optimization (PSO) is a populationbased optimization technique that has been applied to a wide range of problems, but there is little reported in respect of application to scheduling problems because of its unsuitability for them. In the paper, PSO is redefined and modified by introducing genetic operations such as crossover and mutation to update the particles, which is called GPSO and successfully employed to solve the formulated problem. Several benchmarks with fuzzy processing time are used to test GPSO. Through the comparative simulation results with genetic algorithm, the feasibility and effectiveness of the proposed method are demonstrated.