Improved heuristically guided genetic algorithm for the flow shop scheduling problem

Laha, Dipak, and Mandal, Purnendu (2007) Improved heuristically guided genetic algorithm for the flow shop scheduling problem. International Journal of Services and Operations Management, 3 (3). pp. 316-331.

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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.

Item ID: 29436
Item Type: Article (Research - C1)
ISSN: 1744-2389
Keywords: management journals, materials and manufacturing, marketing and services, technical journals
Date Deposited: 08 Oct 2013 03:07
FoR Codes: 15 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 1503 Business and Management > 150301 Business Information Management (incl Records, Knowledge and Information Management, and Intelligence) @ 100%
SEO Codes: 93 EDUCATION AND TRAINING > 9305 Education and Training Systems > 930599 Education and Training Systems not elsewhere classified @ 100%
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