Immune clonal selection algorithm for hybrid flow-shop scheduling problem

In this paper, the mixed-integer nonlinear programming model is established for hybrid flow-shop scheduling problem (HFSP) with the minimum of makespan as the objective function. In order to reduce the computational complexity, immune clonal selection algorithm (ICSA) is applied to HFSP. The definitions of antibody affinity, comparability and density are given in detail. To improve the ability of global optimization for ICSA, mutliclone operator (mutation, crossover and selection) and grouping strategy are employed. The simulation results indicate that ICSA can obtain preferable effect for the solution to HFSP.