Genetic Algorithms to Solve an Industrial Aggregate Production Plan

For any industry, it is mandatory to develop production plans to be executable for a moderate time duration, after the long range corporate decisions on planning strategies, with the reference of long-range forecasts, are developed. Management must work for this intermediate range plan also referred as aggregate production plan, consistently with the long-range policies and resources allocated by long-range decisions. Various essential factors viz., minimizing inventory investment and cost of manufacturing and maximizing profit and service to customers are to be achieved. In today's industrial manufacturing context, virtual planning of manufacturing systems finds the attention of global research activities which is due to their advantages in total elimination of wastages in man hours, materials, money, etc. Mathematical modeling and their simulations are realistic and widely accepted approaches to process various engineering problems Into expected final solutions. Metaheuristics are non-traditional approaches used to optimize various engineering and non-engineering problems. In this paper, an aggregate production-planning problem is modeled with the biologically inspired classical search procedure, Genetic Algorithms. The model is developed to simulate the above problem so as to arrive an effective solution. The implementation procedure is explained step by step and finally the results are analyzed using graphical analyzing software.