LOGISTICS COST OPTIMIZATION MODEL FOR WAREHOUSE ALLOCATION: A CASE STUDY IN THAILAND

The study of logistic cost optimization model development for warehouse allocation concentrates on comparing performances of different techniques in solving set covering problem. The comparison is based on two main criteria: Objective Function Value (OFV) and Computational time. The first approach to be analysed is a mathematical model which is solved by an optimization solver, LINGO. The second method is Greedy Heuristic which is modified and solved in MATLAB. And finally, the Genetic Algorithm available in MATLAB is used for problem solving. The obtained results are compared and analysed in details. To compare the performances, a real base case of set covering problem is introduced. The problem deals with finding suitable warehousing locations in three different regions in order to serve retail stores in Thailand. The numbers of decision variables are ranged from 19,182 to 104,652 and complexity levels are varied in order to compare the performances in handing different complexity problem. Results obtained from these methods are presented.