Enhanced chromosome repairing mechanism based genetic algorithm approach for the multi-period perishable production inventory-routing problem

One of the important aspects of distribution optimization problems is simultaneously, controlling the inventory while devising the best vehicle routing, which is a famous problem, called inventory-routing problem (IRP). When the lot-sizing decisions are jointed with IRP, the problem will get more complicated called production inventory-routing problem (PIRP). To become closer to the real life problems that includes products that have a limited life time like foods, it seems reasonable to narrow down the PIRP problem to the perishable products, which is perishable-production inventory-routing problem (P-PIRP). This paper addresses a P-PIRP in a two echelon supply chain system where the vendor must decide when and how much to produce and deliver products to the customer’s warehouse. Here, the general model of PIRP as mixed integer programming (MIP)is adopted and the perishability constraint are added in order to solve the P-PIRP problems. Due to the complexity of problem, providing solution for the medium to large instances cannot be easily achieved by business applications, and then using the meta-heuristics is unavoidable. The novelty of this research is devising an enhanced genetic algorithm (GA) using multiple repairing mechanisms, which because of its computationally cumbersomeness have absorbed less attention in the literature. The problem runs through some generated instances and shows superiority in comparison to the business application.