Integrated Multi-objective Fuzzy Decision and Planning for Supply Chain Networks
| Autor: | Wen-Cheng Lee, 李文誠 |
|---|---|
| Rok vydání: | 2003 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 92 A multi-product, multi-stage, and multi-period scheduling model is proposed in this paper to deal with multiple incommensurable goals for a multi-echelon supply chain network with uncertain market demands and product prices.We set up fuzzy sets, with monotonic increasing membership functions, to describe the sellers'' and buyers'' preference on sales prices, respectively. The scenario-based approach will be adopted for modeling the uncertain market demands, however, the realization of objective values might be unacceptably low for certain scenarios.That is, the related decisions lack robustness.Thus, we propose the lower partial mean as the measure of robustness, and include it as part of objectives. The supply chain scheduling model is constructed as a mixed-integer nonlinear programming problem to satisfy several conflict objectives, such as fair profit distribution among all participants, safe inventory levels, maximum customer service levels, and robustness of decision to uncertain product demands, therein the compromised preference levels on product prices from the sellers and buyers point of view are simultaneously taken into account. For purpose that a compensatory solution among all participants of the supply chain can be achieved, a two-phase fuzzy decision-making method is presented. In phase one, use the minimum operator to maximize the degree of satisfaction for the worst situation.Then, apply the product operator to maximize the overall satisfactory level with guaranteed minimal fulfillment in phase two. Several numerical examples illustrate that the proposed two-phase method can provide a better compensatory solution. And the inclusion of robustness measures as part of objectives can significantly reduce the variability of objective values to product demand uncertainties. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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