Solution for flow shop scheduling problems using chaotic hybrid firefly and particle swarm optimization algorithm with improved local search

Scheduling is important for the efficient use of resources in the production and service sectors. Depending on the sector and production environment, scheduling problems can vary greatly. Flow Shop production environments are a common feature of industrial activity. In these production environments, m individual machines are used to process n jobs. As the number of jobs and number of machines employed increases, so does the difficulty of finding an accurate solution to scheduling problems. For this reason, a variety of heuristic and metaheuristic solution methods have been developed for this type of problems. In this study, chaotic hybrid firefly and particle swarm optimization are used with a developed version of local search for scheduling of flow shop production environments. Maximum completion time was taken as the objective function. In order to develop the solutions reached, the initial solution was adapted with NEH method. The proposed method was applied to the problem sets in the literature and the results obtained compared with other methods. The experimental results produced by the proposed algorithm were found to be more reliable than those of other algorithms in the literature.