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A modified immunoglobulin-based artificial immune system algorithm for solving the permutation flow shop scheduling problem

Abstract To minimize makespan in the permutation flow shop scheduling problem, a modified immunoglobulin-based artificial immune system algorithm (M-IAIS) is developed to search for a job sequence. The basic structure of immunoglobulin-based artificial immune system algorithm consists of three parts, somatic recombination, hypermutation, and isotype switching. A special process, named B cell repertoire updating, is considered in M-IAIS algorithm to accelerate the convergence speed. Taillard’s benchmark problems are chosen as test instances. Percentage deviation, hypothesis test, convergence performance, and robust analysis are considered in the paper to evaluate the performance of M-IAIS algorithm. Computational results show that M-IAIS algorithm is competitive for the permutation flow shop scheduling problem.