A robust optimization approach for the production-routing problem with lateral transshipment and outsourcing

Abstract

Despite the fact that there is a large body of literature on the Production Routing Problem (PRP), we were struck by the dearth of research on outsource planning and lateral transshipment. This paper presents a mixed-integer linear programming model for incorporating outsourcing, lateral transshipment, back ordering, lost sales, and time windows into production routing problems. Then a robust optimization model will be introduced to overcome the detrimental effects of demand uncertainty. Considering the scale and complexity of the suggested problem, addressing it in a reasonable time was a challenge. Therefore, three matheuristic algorithms, including Genetic Algorithm (GA), Simulated Annealing (SA), and Modified Simulated Annealing (MSA), are developed for solving large-scale problems. Eventually, computational experiments on disparate instances are performed, and the results show the effectiveness and efficiency of the proposed algorithms. In other words, our recommended algorithms outperform the CPLEX solver in terms of the quality and time of obtaining the solutions.