Improved heuristically guided genetic algorithm for the flow shop scheduling problem

Improved heuristically guided genetic algorithm for the flow shop scheduling problem

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Article ID: iaor2008151
Country: United Kingdom
Volume: 3
Issue: 3
Start Page Number: 316
End Page Number: 331
Publication Date: Jul 2007
Journal: International Journal of Services and Operations Management
Authors: ,
Keywords: heuristics: genetic algorithms
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 gives superior results when compared with the simulated annealing from the literature.

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