A decision support system for consolidated distribution of a ceramic sanitary ware company

This study proposes a model-driven decision support system (DSS) for a consolidated distribution problem of a ceramic sanitary ware company with two factories producing different types of products. The primary motivation for consolidating loads of the these factories is to better use the empty capacity of the vehicles in terms of weight and volume. For transportation, the company has made contracts for each factory with a third-party logistics provider. In these contracts, there are special conditions according to the characteristics of the products. We suggest two kinds of transportation approaches that determine how to combine loads of two factories and how to solve the routing problem that arises to distribute the remaining loads. The DSS includes a mathematical model that determines full-truck loads and a hybrid genetic algorithm that solves the open vehicle routing problem. Both of these approaches have been developed specifically for the problem within the scope of the study. The mathematical model provides the best use of vehicles in terms of volume and weight. At the same time, the meta-heuristic approach offers the opportunity to address the complex cost structure of the emerging routing problem. The proposed DSS receives all order data from the enterprise resource planning system and constructs a dynamic distribution problem. Then it generates solution alternatives by using the models developed in this study and presents cost-effective and visualizable distribution plans.