Minimizing makespan in job-shop scheduling problem using an improved adaptive particle swarm optimization algorithm

This paper proposes an improved adaptive particle swarm optimization algorithm (IAPSO) for the minimization of makespan in job shop scheduling problems (JSP). Inspired by hormone modulation mechanism, an adaptive hormonal factor (HF) is designed to be used in the updating equations of particle swarm. Using the HF, each particle of the swarm can adjust its particle position self-adaptively to avoid the premature phenomena and get better solution. Computational experiments demonstrate that the proposed IAPSO reaches high-quality solutions in short computational times. By employing IAPSO, machines can be used more efficiently, which means tasks can be allocated appropriately, production efficiency can be improved, and the production cycle can be shortened efficiently.