This paper considers the problem of permutation flowshop scheduling with the objectives of minimising the makespan and total flowtime of jobs, and presents an Improved Genetic Algorithm (IGA). The initial population of the genetic algorithm is created using the popular NEH constructive heuristic (Nawaz et al., 1983). In IGA, multi-crossover operators and multi-mutation operators are applied randomly to subpopulations divided from the original population to enhance the exploring potential and to enrich the diversity of the crossover templates. The performance of the proposed algorithm is demonstrated by applying it to benchmark problems available in the OR-Library. Computation results based on some permutation flowshop scheduling benchmark problems show that the IGA gives better solution when compared with the earlier reported results.
Flowshop scheduling, Makespan, Total flowtime, Genetic Algorithm
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