Blocking Flow Shop Scheduling Problems Using Evolution Strategies Algorithm

Flow shop scheduling problems with blocking (BFSSP) have ample applications in the industry. In this paper, an Evolutionary algorithm, i.e. Evolution Strategies (ES) is used to minimize the makespan of BFSSP. The initial solution is randomly generated which acts as a seed for the ES algorithm. In reproduction (1+5)-ES is used, hence five offspring are generated from a single parent. Since mutation is the main source of genetic variation, therefore multi-mutation operators are used for inducing randomness in the solution. Both insert and swap mutations are used in alternate iterations. In selection, (
$\mu+ \lambda$
)-ES is used, hence a good parent solution can survive many iterations unless superseded by a better offspring. The technique is tested on benchmark problems of Taillard, and results are compared with other available techniques in the literature. Results show that the ES performs better for BFSSSP in terms of solution quality.