Design of manufacturing cells in the presence of alternative cell locations and material transporters
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Design of manufacturing cells in the presence of alternative cell locations and material transporters R Logendran* and Y Karim Oregon State University, Corvallis, OR, USA This paper addresses two significant issues in the design of cellular manufacturing (CM) systems: (i) the availability of alternative locations for a cell, and (ii) the use of alternative routes to move part loads between cells when the capacity of the material transporter (MT) employed is limited. In addition, several other important factors in the design of CM systems including machine capacity limitations, batches of part demands, non-consecutive operations of parts, and maximum number of machines assigned to a cell are considered. A nonlinear programming model, comprised of binary and general integer variables, is formulated for the research problem. A higher-level heuristic solution algorithm based upon a concept known as ‘tabu search’ is presented for solving industry-size problems. Six different versions of the heuristic are developed to investigate the impact of long-term memory and the use of fixed versus variable tabu-list sizes. Explicit method-based techniques are developed to convert the original nonlinear programming model into an equivalent mixed (binary)-integer linear programming model in order to test the efficacy of the proposed solution technique for solving small problem instances. The solutions obtained from the heuristics have average deviation of less than 3% of the optimal solutions, and require less than a minute in comparison with optimizing methods that needed 1–10 h of computation time. A carefully designed statistical experiment is used to compare the performance of the heuristics by solving three different problem structures, ranging from four to 30 parts, and three to nine locations. The experiment shows that as the problem size increases, the tabu-search-based heuristic using fixed tabu list size and long-term memory based on minimal frequency strategy is preferred over the other heuristics. Journal of the Operational Research Society (2003) 54, 1059–1075. doi:10.1057/palgrave.jors.2601608 Keywords: cellular manufacturing; nonlinear integer programming; mathematical modeling; optimization; heuristics
Introduction The application of cellular manufacturing (CM) in small to large size parts manufacturing companies has resulted in significant increase in manufacturing productivity. It has contributed to a variety of savings with the most notable being the reduction in setup time, throughput time and work-in-process inventories, simplified flow of parts and tools, and centralization of responsibility.1–3 Two distinct issues that have not been addressed in the published literature motivate the research reported in this paper. First, previous investigations have assumed that a key machine assigned to a cell permanently identifies its location, thus foregoing the opportunity of clustering with machines assigned to other
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