A genetic algorithm for permutation flowshop scheduling with total flowtime criterion

This paper presents a genetic algorithm (GA) for the permutation flow shop scheduling problem with the objective of minimizing total flowtime. An initialization method based on the LR heuristic is used to construct an initial population with a certain level of quality and diversity. A variable-neighborhood-search based local improvement is utilized to refine all the generated solutions in each generation. A comparative evaluation is carried out against some effective algorithms in recent literature. The results show that the proposed GA is very effective for the permutation considered.