A neuro-tabu search heuristic for the flow shop scheduling problem

Authors:
M. Solimanpur;P. Vrat;R. Shankar
Affiliations:
Mechanical Engineering Department, Indian Institute of Technology Delhi, Hauz Khas, New Delhi-110 016, India;Director, Indian Institute of Technology Roorkee, Roorkee-247 667, Uttaranchal, India;Department of Management Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi-110 016, India
Venue:
Computers and Operations Research
Year:
2004

Citing 4
Cited 8

Future paths for integer programming and links to artificial intelligence

Computers and Operations Research - Special issue: Applications of integer programming
The application of the simulated annealing algorithm to the solution of the n/m/Cmax flowshop problem

Computers and Operations Research
A genetic algorithm for flowshop sequencing

Computers and Operations Research - Special issue on genetic algorithms
Tabu Search

Tabu Search

A review on evolution of production scheduling with neural networks

Computers and Industrial Engineering
A tabu search algorithm for the flowshop scheduling problem with changing neighborhoods

Computers and Industrial Engineering
An improved NEH heuristic to minimize makespan in permutation flow shops

Computers and Operations Research
A neuro-tabu search algorithm for the job shop problem

ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
A heuristics method based on ant colony optimisation for redundancy allocation problems

International Journal of Computer Applications in Technology
Ant colony optimization algorithm for a Bi-criteria 2-stage hybrid flowshop scheduling problem

Journal of Intelligent Manufacturing
Integration of artificial neural networks and genetic algorithm for job-shop scheduling problem

ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Neuro-genetic impact on cell formation methods of Cellular Manufacturing System design: A quantitative review and analysis

Computers and Industrial Engineering

Quantified Score

Hi-index	0.01

Visualization

Abstract

Flow shop scheduling deals with the sequencing of different jobs that visit a set of machines in the same order. A neural networks-based tabu search method, namely EXTS, is proposed for the flow shop scheduling. Unlike the other tabu search-based methods, the proposed approach helps diminishing the tabu effect in an exponential way rather than most commonly used way of diminishing it in a sudden manner. On the basis of the conducted tests, some rules are evolved to set the values for different parameters. The effectiveness of the proposed method is tested with 23 problems selected from literature. The computational results indicate that the proposed approach is effective in terms of reduced makespan for the attempted problems.