The multi-product, economic lot-sizing problem in flow shops: the powers-of-two heuristic

Abstract This paper presents a new and efficient heuristic to solve the multi-product, multi-stage, economic lot-sizing problem. The proposed heuristic, called the powers-of-two method, first determines sequencing decisions then lot sizing and scheduling decisions are determined. This method assumes that cycle times are integer multiples of a basic period and restricts these multiples to the powers of two. Once time multiples are chosen, we determine for each basic period of the global cycle the set of products to be produced and the production sequence to be used. Then a non-linear program is solved to simultaneously determine lot sizes and a feasible production schedule. To evaluate its performance, the powers-of-two method was compared to both the common cycle method and a reinforced version of the job-splitting heuristic. Numerical results show that the powers-of-two method outperforms both of these methods. Scope and purpose The multi-product, multi-stage, economic lot-sizing problem studied in this paper is the problem of making sequencing, lot-sizing and scheduling decisions for several products manufactured through several stages in a flow shop environment so as to minimize the sum of setup and inventory holding costs while a given demand is fulfilled without backlogging. This problem and similar problems are met in many different industries like the food canning industry, the appliance assembly facilities or in beverage bottling companies. The most commonly used approach to deal with this problem is the common cycle approach where a lot of each product is produced each cycle. A few other approaches are also proposed. In this paper we propose a new and more efficient solution approach that assigns different cycle times to different products.

[1]  H. Taha,et al.  The Economic Lot Sizes in Multistage Production Systems , 1970 .

[2]  S. Goyal Note—Note on “Manufacturing Cycle Time Determination for a Multi-Stage Economic Production Quantity Model” , 1976 .

[3]  M. K. El-Najdawi Multi-cyclic flow shop scheduling: An application in multi-stage, multiproduct production processes , 1997 .

[4]  Jose Andere-Rendon Economic lot size determination in finite production rate multi-stage assembly systems under power-of-two policies , 1990 .

[5]  Paul R. Kleindorfer,et al.  Common cycle lot-size scheduling for multi-product, multi-stage production , 1993 .

[6]  A. Z. Szendrovits Manufacturing Cycle Time Determination for a Multi-Stage Economic Production Quantity Model , 1975 .

[7]  Graham K. Rand,et al.  Decision Systems for Inventory Management and Production Planning , 1979 .

[8]  P. A. Jensen,et al.  Scheduling in a Multistage Production System with Set-up and Inventory Costs , 1972 .

[9]  M. K. El-Najdawi A job-splitting heuristic for lot-size scheduling in multi-stage, multi-product production processes , 1994 .

[10]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[11]  A. Z. Szendrovits Note—On the Optimality of Sub-Batch Sizes for a Multi-Stage EPQ Model—A Rejoinder , 1976 .

[12]  Jaya P. Moily,et al.  Optimal and heuristic procedures for component log-splitting in multi-stage manufacturing systems , 1986 .

[13]  John I. S. Hsu,et al.  Common cycle scheduling in a multistage production process , 1990 .