Simulated Annealing and Direct Search based Optimization Models for Facility Location in Logistic Network Design

Finding the optimum location of facilities is an important problem related in logistics. Locations of Distribution Centers (DCs) can be at the proximity of highways and closer to populated areas in order to speedup package deliveries and minimize the overall transport cost and time. Deciding the optimum number of DCs as well as the optimum location of DCs are the most important aspects of the design of any logistics network. Deciding the number of DCs will depend upon the budget and optimum locations of DCs will reduce the overall transport cost. As operations globalize, location decisions become more complex. A powerful approach to analyzing these problems is the transportation method of linear programming. The linear programming based methods will take much time to attain a solution in such a wide problem space. But for dealing with such wide problem space, soft computing based approaches are well suited and can find a meaningful solution in finite time. This work generate the Simulated Annealing and Direct Search based model for facility location in logistics and evaluate its performance. Also, compare the performance of this model with a k-mean clustering based model.