An Effective Hybrid Particle Swarm Optimization for Flexible Job Shop Scheduling Problem

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An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem

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An Effective Hybrid Particle Swarm Optimization for Flexible Job Shop Scheduling Problem

The job shop scheduling problem is one of the most arduous combinatorial optimization problems. Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. This paper proposed a new effective approach based on the hybridization of the particle swarm optimization (PSO) an...

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An effective hybrid particle swarm optimization algorithm for flexible job- shop scheduling problem

Flexible job-sop scheduling problem (FJSP) is based on the classical job-shop scheduling problem (JSP), however, it is even more harder than JSP because of the machine selection process in FJSP. In this paper, a particle swarm optimization (PSO) algorithm and a tabu search (TS) algorithm are integrated to solve the FJSP, the objective is to make the complete time minimum, i.e., to get the best ...

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Hybrid Multi-Objective Particle Swarm Optimization for Flexible Job Shop Scheduling Problem

Hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated annealing (SA) is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hy...

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ژورنال

عنوان ژورنال: The Open Automation and Control Systems Journal

سال: 2014

ISSN: 1874-4443

DOI: 10.2174/1874444301406011604