A genetic algorithm for flowshop scheduling with multiple objectives

In this paper, we study the permutation flowshop scheduling problem with the objectives of minimizing the makespan and total flowtime of jobs. An attempt is made to solve the multi-objective problem by using the Proposed Genetic Algorithm (ProGA). In order to evaluate the ProGA, we have made use of benchmark flowshop scheduling problems, and the heuristically non-dominated solutions for these problems are obtained from each of the existing methodologies and the ProGA. These non-dominated solutions are combined to obtain a net heuristic non-dominated front for a given problem. It is found that most of the solutions on the net non-dominated front are yielded by the ProGA, bringing out the superiority of the proposed genetic algorithm.