Hybrid Genetic Algorithm for Advanced Planning and Scheduling

In this paper, advanced planning and scheduling (APS) in which each customer order has an absolute due date and outsourcing is available in a manufacturing supply chain is addressed. An integer programming model is presented to solve the APS problem. The objective is to minimize the makespan of each customer order while satisfying the due date constraints. The proposed model considers the integration of planning and scheduling, alternative process plans for job types, machine selection, and the precedence constraints of job operations as well. A hybrid algorithm integrating genetic algorithm and simulated annealing is proposed to solve the model. A numerical experiment is carried out to demonstrate the efficiency of the proposed algorithm. A relatively good production plan is obtained. The results indicate that the hybrid genetic algorithm outperforms current algorithms in the literature.