A shuffled frog-leaping algorithm for hybrid flow shop scheduling with two agents

Two-agent scheduling problem has attracted much attention; however, two-agent hybrid flow shop scheduling problem (TAHFSP) is seldom studied. In this study, TAHFSP and its minimality model are considered and a novel shuffled frog-leaping algorithm (SFLA) is proposed is to minimize the sum of the objectives of two agents. The following new principles are applied in SFLA: a tournament selection based method is used to divide population, not all solutions of population are allocated into memeplexes, the best solution of each memeplex acts as the object of the search process and the search process within memeplex consists of the global searches on two sub-problems sequentially and multiple neighborhood search. We test the performance of SFLA using a number of instances and the experimental results show the notable advantage of our SFLA when compared to other algorithms of TAHFSP.