A Practical Scheduling Optimizer for Plastic Injection Molding Facilities

Scheduling of plastic injection molding facilities has been a very important issue in operations research and optimization field. This paper presents the development and experimentation of new optimization approach for production planning and scheduling. It focuses on parallel machine scheduling problems in plastic injection molding facility in Egypt. A genetic algorithm, a cuckoo search, and a mixed-integer linear programming (MILP) approach were adapted to solve the problem. Multiple experiments were conducted to compare these approaches. An improved MILP solution approach was proposed, and it outperformed the other optimizers in terms of solution accuracy and computational time. Based on this work, a novel scheduling tool based on MATLAB and MS-Excel was developed to help practitioners generate optimum schedules with less computational time. The authors addressed the scheduling optimization problem from both theoretical and practical perspectives and the outcomes of this research are beneficial for both research and industry. © 2020 IEEE.