Multiperiod multiple-item dynamic lot sizing problem when discounts are available Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/bv73c298w

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  • This thesis extends Wagner-Whitin's Planning Horizon Theorem to discount situations in multiperiod multiple-item dynamic lot sizing problems. Three heuristic techniques are developed using the Least Unit Cost Method, Silver-Meal Method, and Inoue-Chang Method. The three techniques are described and compared in terms of their effectiveness in dealing with the dynamic lot sizing problem. These techniques are modified in order to apply to single-item discount situations. The performance of these modified techniques are tested by using Kaimann's data with discount data added and 100 additional sets of randomly generated data. A heuristic program has been developed for each of the three methods. Each program is designed to handle joint-order multiperiod, multiple-item dynamic lot sizing problems. In addition, both no discount and with discount situations are studied in the development of each program. All the above programs were first developed under the assumption that no split orders occurred. A mathematical programming model was then developed for the situations where the split orders were allowed. The difficulties involved in searching solutions using the mixed integer programming model are discussed. A two-item problem with one discount level is selected to illustrate the developed programs. The performance of the heuristic programs are measured and estimated through the use of dynamic programming techniques applied to some selected special situations as benchmarks. The comparisons of performance of the heuristic programs among themselves are also conducted based upon the costs of reaching solutions and the optimality of the solutions reached by using those programs. In our testing examples, the average costs of solutions reached by the heuristic methods based upon the Least Unit Cost Method, Silver-Meal Method, and Inoue-Change Method are -$560.9, -$1475.28, and -$1742.36 respectively. The average CPU times for each heuristic program to reach a solution for a 12-period two-item single discount problem are 0.052 sec., 0.064 sec., and 0.054 sec. respectively. A conclusion is reached that the heuristic program based upon the Inoue-Chang Method has significant advantages over other programs.
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-10-15T15:35:32Z (GMT) No. of bitstreams: 1 ChangChiaHao1979.pdf: 1837264 bytes, checksum: 4b1f3f7cd1ca9bb2fabca9ed009147d6 (MD5)
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