Hybrid solving algorithm for complex machine scheduling problem

In this research, we make use of one of the multiple objective decision-making methods, min-max technique, to develop a new hybrid metaheuristic for solving sequence-dependent setup time hybrid flowshop scheduling problems with consideration of two performance measures, namely C_max, and sum of the earliness and tardiness, simultaneously. The proposed hybrid approach comprises three components: an initial population generation method based on an ant colony optimization (ACO), a simulated annealing (SA) as an evolutionary algorithm employs certain probability to avoid becoming trapped in a local optimum, and a variable neighborhood search (VNS) which involves three local search procedures to improve the population.