Title: Improved heuristically guided genetic algorithm for the flow shop scheduling problem

Authors: Dipak Laha, Purnendu Mandal

Addresses: Mechanical Engineering Department, Jadavpur University, Kolkata, India. ' Information Systems and Analysis Department, College of Business, Lamar University, Beaumont, TX 77710, USA

Abstract: This paper deals with the problem of scheduling on makespan criterion in the flow shop environment. We have presented a new heuristic genetic algorithm (NGA) that combines the good features of both the genetic algorithms and heuristic search. The NGA is run on a large number of problems and its performance is compared with that of the Standard Genetic Algorithm (SGA) and the well-known Nawaz-Enscore-Ham (NEH) heuristic. The NGA is seen to perform better in almost all instances. The complexity of the NGA is found to be better than that of the SGA. The NGA also performs superior results when compared with the simulated annealing from the literature.

Keywords: flow shop scheduling; genetic algorithms; GA; simulated annealing; SA; Nawaz-Enscore-Ham heuristic; NEH; heuristics; makespan criterion.

DOI: 10.1504/IJSOM.2007.013095

International Journal of Services and Operations Management, 2007 Vol.3 No.3, pp.316 - 331

Published online: 07 Apr 2007 *

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