GENETIC ALGORITHM APPROACH FOR ANALYSIS OF MULTI ITEM MULTI PERIOD PROCUREMENT LOT SIZING PROBLEM

This paper approaches Genetic algorithm for multi objective optimization of the multi item multi period procurement lot sizing problem. A mathematical model is developed to simulate raw material procurement lot sizing analysis for a real time valve manufacturing company. Model takes into account the constraints imposed by the budget, maximum order quantity and limited warehouse space. The analysis is aimed at arriving at optimum order quantities for the different periods so that the total cost is minimized. Since the developed mathematical model is NP hard due to the mixed binary integer programming nature, GA is used to for the analysis. A hybrid non-dominated sorting genetic algorithm is applied for multi objective optimization. Pareto fronts obtained from GA are compared with solutions obtained from commercial software like LINGO to establish that GA are more reliable and give better optimality.