Powerful Biogeography-Based Optimization Algorithm with Local Search Mechanism for Job Shop Scheduling Problem with Additional Constraints

Abstract

AbstractThis paper proposes a Hybrid Biogeography-Based Optimization algorithm for solving the Job shop Scheduling Problem with additional constraints of Time Lags and transportation time using a Single Transport Robot to minimize the makespan (Completion time of the last operation executed). Biogeography-Based Optimization (BBO) algorithm is an evolutionary algorithm inspired by the mi-gration of species between habitats. It has successfully solved optimization prob-lems in many different domains and has demonstrated excellent performance. In order to improve the optimization efficiency of BBO algorithm, the Greedy con-structive heuristic is used for population initialization to guarantee the diversity of solutions and the local search metaheuristic is used for the mutation step. The ef-ficiency of the proposed algorithm is demonstrated by using new set of bench-marks for the problem. Numerical results show that the proposed Hybrid BBO algorithm not only significantly improves the performance of the standard BBO algorithm, but also finds competitive results compared with recently developed optimization methods.