Integrating Vehicle Routing With Cross Dock In Supply Chain
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This article provides a unified mathematical model of cross dock with vehicle routing in supply chain and the model is using tabu search. This study, in terms of purpose is applied and the method of data collection is descriptive. In this study, data collection of theses and articles are extracted, including location coordinates of cross dock, suppliers and customers and demand of supplier and customer for each pair. In order to achieve the goal of a mathematical model for the problem to minimize the total distance traveled objectives and maximize customer demand has been answered were presented. Since the problem is NP-Hard, we need to solve the model through methods such as Tabu Search meta-heuristic such as lead; this was done by software Matlab. To realize the accuracy and efficiency of the model, problems with small size (less than 200 seconds solution time) and medium size (solution time between 200 and 1000 seconds) was designed. By solving these problems became clear that the model is the necessary performance. Software issues exact solution able to solve them in less than 200 seconds was among the small issues have been Classification (runtime ≤ 200). According to resolve the issues, growth in complexity and time is required by the software solution to boost car and customers. For an average size of software issues with the exact solution used in this study GAMS IDE / Cplex's ability to solve problems within 1,000 seconds show. The results also showed a considerable scatter in the time needed to resolve these issues so that the time is variable between 289.8 and 998.2 seconds and average amounts to 579.3 seconds. Then Algorithm for consolidated performance in comparison with results from software GAMS IDE /Cplex compared with each other to solve small and medium investigated. According to the results obtained in solving the problems of small and medium-sized meta-heuristic has been shown to have an efficient performance.