A Hybrid Genetic Algorithm for Type-2 Fuzzy Job Shop Scheduling Problem

This paper discusses a job shop scheduling problem with interval type-2 fuzzy processing times (IT2FSJSP). The objective is to minimize the makespan. A hybrid genetic algorithm with simulated-annealing operators (HGAS) is proposed to solve the problem discussed. The HGAS has the following features: (i) a heuristic initialization is designed by combining four heuristics to generate high-quality solutions. (ii) a parameter adaption strategy is proposed to automatically adjust probabilities of crossover and mutation according to population size and the number of iterations. (iii) two crossover operators are used to search solution in various directions to increase the likelihood of finding better solutions. The simulation results indicate that the HGAS is effective for IT2FSJSP.