A social spider optimization algorithm for hybrid flow shop scheduling with multiprocessor task

Hybrid flow shop scheduling with multiprocessor task (HFSPMT) is a strongly NP-hard problem that has a wide range of applications in several real-life industrial environments. Due to its essential complexity and practical relevance, HFSPMT has been of an increasing interest for researchers and industrialists in the last two decades. Social spider optimization (SSO) is a recent swarm intelligence algorithm that has been rarely applied on combinatorial optimization problems. In order to make a small step toward having an idea about its effectiveness in solving combinatorial optimization, in this work, a new SSO algorithm is proposed to solve HFSPMT problem with the objective of makespan minimization. The proposed algorithm is experimented on benchmark instances and compared with other existing swarm intelligence algorithms in the literature. The obtained results and the comparisons show that the performance of the proposed algorithm is highly competitive in terms of solution quality

کلیدواژه ها:

Metaheuristics ، multistage hybrid flow shop ، multiprocessor tasks ، social spider optimization