A Strategic Capacity Planning Model: A Genetic Algorithm Approach (International Journal of Engineering and Computer Science, 2013)
This paper presents an optimization based method to overcome the demands for multi-period production capacity planning by identifying the resources for the future months. Capacity planning plays an important role in all the manufacturing companies. The demand which has been forecasted by the company is totally delivered to the customers by the perfect production planning. Here we use Genetic Algorithm as the optimization tool for finding the optimal solution to minimize the production cost for six months to maximize the profit. The production cost must be minimized as much as possible and Inventories levels should be perfectly maintained, so the profit will be automatically increased. The inventory management also plays an important role in supply chain management. Inventory optimization is the real time works for the engineers those who are in the top administrative level. So here we concentrate on the main costs like Material cost, Inventory cost, Marginal cost of backlog, Hiring and Training cost, Lay-off cost, Regular time cost, Over time cost and cost of sub-contracting for allocating it by considering the demands of six months. Here we focus on generating an optimal schedule for the production for six months by fixing forty eight variables.