Karşılanamayan talepli çoklu ürün envanter yerleşim rotalama problemi

The design of an effective logistic network generally consists of two combinatorial optimization problems; to determine facility locations among a group of potential candidates, and determine vehicle routes to supply demand points from these locations. The combination of these two problems is known as the Location-Inventory-Routing Problem (LIRP) and this study addresses the multi-product and multi-depot LIRP while considering defective manufacturing processes. LIRP is an enriched location-routing problem (LRP) with the inventory related issues and determines inventory, location and transportation related decisions at the strategic, tactical and operational levels. This study considers a manufacturing process with the probability of encountering defective items in every supply point. Because of these defective items supply of products may disrupted in supply points and, therefore, backorders may occur. A mathematical model, a combination of a location-routing problem and a joint replenishment economic order quantity (EOQ) model with backorders, is developed to formally describe the problem. Considering the NP-hardness of the proposed model, a hybrid meta-heuristic algorithm, a combination of the adaptive large neighborhood search (ALNS) algorithm and the variable neighborhood search (VNS) algorithm, is proposed to tackle the problem. Since there is a lack of standard benchmarks related to the considered LIRP problem in the literature the performance of the proposed algorithm is evaluated on a standard benchmark set of LRP instances taken from the related literature, and the proposed algorithm is realized on a real-life problem. The computational results indicate the efficiency of the proposed algorithm in solving the LRP instances and the proposed algorithm could be successfully used to handle the LIRPs.