ACTIVITY-BASED CAPACITY EXPANSION MODEL AND HEURISTIC ALGORITHM USING BEAM SEARCH
Planning for capacity expansion is a crucial activity of the strategic-level decision making in company to support the anticipated demand growth. With the development of manufacturing technologies and managerial methods, such as the advent of cellular manufacturing and Activity-based Costing (ABC), some aggregate production planning and capacity expansion models require to consider production processes and activity centers. In this paper, the authors develop a capacity expansion model considering structured production processes. The model can make production planning decisions and capacity expansion decisions simultaneously, including determining the quantity of final products and semi-products, and determining the optimal capacity adjustment policy. The authors also assume that activity efficiencies including unit activity cost, activity consumption for producing one unit product, and capacity of activity cells are time-varying and related to the longevity of activity cell. Considering the difficulty in solving the capacity expansion model that is a Mixed Integer Linear Programming (MILP), A Beam Search (BS) algorithm for the solution is proposed, and this algorithm is proved to be effective through the computational study in this paper.
capacity expansion heuristic activity-based beam search
Renqian Zhang Lankang Zhang
School of Economics and Management, Beihang University, Beijing 100191, China
国际会议
The Tneth International Conference on Industrial Management(第十届工业管理国际会议 ICIM 2010)
北京
英文
64-70
2010-09-16（万方平台首次上网日期，不代表论文的发表时间）