Heuristic solution of lot-sizing: an industrial case study

Abstract

Lot size inventory control problem with ambiguous variable demand is important in industry as inventories can be a major commitment of monetary resources and affect virtually every aspect of daily operations. Inventories can be an important competitive weapon and are a major control problem in many companies, and improper lot sizes can affect the inventory levels and the costs associated with them. Typically, a manufacturing firm will have one-third of its assets invested in inventory. Inventory control is concerned with the management of this investment. But at the same time in manufacturing firm, production wants efficient operation. This implies large production orders which generate large inventories to reduce machine setup and limited lotsize per setup. So the intense international competition in manufacturing has provided a strong incentive to management to seek new, more effective ways of managing production to maintain or achieve a competitive edge. As a result, thousands of companies have implemented Computer based production and inventory control systems. One of the ways to control inventory is to control lot-size. The objective of the research is to find a lot-sizing strategy that satisfies the demands for all items over the entire horizon without backlogging, and that minimizes the sum of inventory-carrying costs, fixed-order costs. All demands, cost parameters, and capacity limits may be time dependent. The current research work has been directed toward the development of a model for multi-item problem considering these parameters. The models have been executed with data of a garment industry in Bangladesh.