A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO

Nowadays, rapid changes in customers' demands have redoubled the importance of new concepts such as supply chain flexibility and its application. The extent to which flexibility should be built into supply chains requires full consideration. Flexibility is defined as firms' quick and efficient response to changes. This paper quantifies the positive effects of adding different flexibility dimensions to a production planning bi-objective mathematical model. Four flexibility dimensions are proposed according to the needs of a production plant chosen as the case study. The objective functions are to minimize total costs along with the delivery time of the product, respectively. We also employ two metaheuristic algorithms, NSGA-II and MOPSO, to solve our proposed NP-hard model. Afterwards, we compare both solution strategies based on five criteria to achieve optimal results. Moreover, we compare the performance of both flexible and inflexible models in terms of costs. The results show that applying the flexible model causes a reduction of %22 in costs.

Automated summary

This study examines the impact of adding flexibility dimensions to production planning on costs and delivery time. Two metaheuristic algorithms are used to solve the problem. The results demonstrate a significant cost reduction when applying the flexible model.