Warehouse Location Problems for Single Commodity by Different Method

Facility location problems are traditionally investigated with the assumption that all the clients are to be provided service. A significant shortcoming of this formulation is that a few very distant clients, called outliers, can exert a disproportionately strong influence over the final solution. What makes the problems harder is that we have to also select the subset that should get service. We provide generalizations of various approximation algorithms to deal with this added constraint.The mixed integer-linear models that have been used in most analyses of warehouse location problems fail to capture the potential operating efficiencies associated with large scale facilities. Here we present an algorithm for finding a minimal cost warehouse system design wherein individual warehouses have limited capacities and exhibit economies of scale. The iterative procedure defines and solves a series of conventional transportation problems in order to converge on the optimal system design. The algorithm is well suited to solving large problems of the type commonly encountered in practice.