Solving Single Stage Uncapacitated Warehouse Location Problem by a Combination of OR Based Heuristics and Genetic Algorithm: An Empirical Investigation

摘要

In this paper Single Stage Un-capacitated Warehouse location Problem is solved using Genetic Algorithm. Heuristics are developed to generate initial population on the basis of strong Linear Programming (LP) relaxation. Sample problems are solved for four problem sizes; and four combinations are tested which are based on different crossover and mutation schemes. It is observed that circular mutation provides a good balance between computation time and optimality gap. It is found that GA works well even for small population size and less number of generations. The solutions obtained from GA are found to be very near to the optimum solution (within 1 percent) even at the end of the first generation of GA. GA results are compared with results obtained by solving strong formulation of SSUWLP using GAMS and t-tests are performed. GA combined with heuristic based starting solution is slower than GAMS for problem instances of small size but shows very good results with increase in problem size.