Flexible job shop scheduling using a multiobjective memetic algorithm

Authors:
Tsung-Che Chiang;Hsiao-Jou Lin
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan, R.O.C.
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

Citing 15
Cited 1

Routing and scheduling in a flexible job shop by tabu search

Annals of Operations Research - Special issue on Tabu search
A fast taboo search algorithm for the job shop problem

Management Science
A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems

Computers and Industrial Engineering
A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems

Computers and Operations Research
Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems

Computers and Industrial Engineering
A genetic algorithm for the Flexible Job-shop Scheduling Problem

Computers and Operations Research
Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling

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

Computers and Industrial Engineering
Flexible job-shop scheduling with parallel variable neighborhood search algorithm

Expert Systems with Applications: An International Journal
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems

Computers and Industrial Engineering
An artificial immune algorithm for the flexible job-shop scheduling problem

Future Generation Computer Systems
Parallel hybrid metaheuristics for the flexible job shop problem

Computers and Industrial Engineering
An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems

Computers and Industrial Engineering
Approach by localization and multiobjective evolutionaryoptimization for flexible job-shop scheduling problems

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

A memetic algorithm for the multi-objective flexible job shop scheduling problem

Proceedings of the 15th annual conference on Genetic and evolutionary computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used in the parts of genetic algorithm and local search, respectively. The local search procedure follows the framework of variable neighborhood descent algorithm. The proposed algorithm is compared with three benchmark algorithms using fifteen classic problem instances. Its performance is better in terms of the number and quality of the obtained solutions.