| Summary: | 博士 === 國立臺灣科技大學 === 工業管理系 === 101 === Due to the intense global competition, businesses generally adopt a time-based competition strategy to speed a fulfillment plan in order to meet customer demands. In addition, the inventory should be reduced and maintained at a proper stock level for the purposes of better business performance and customer satisfaction.
The function of production planning is to deal properly with demand fluctuations by using overtime, inventory, subcontracting, and backordering, or changing the workforce level to meet the customers’ needs. An aggregate plan aligns the production runs with the sales orders and simultaneously achieves multiple business objectives such as minimizing the total cost, maximizing the profit, minimizing the change in workforce level, and so on.
This thesis formulates a novel fuzzy multi-level multi-objective production planning (FMLMOPP) model for a supply chain under a fuzzy environment. The multi-level (e.g., three-level) supply chain consists of a wholesaler, a manufacturer (the core member of the supply chain), and a supplier, as well as limited resources (i.e., workforce, capacity, and/or storage space) of each member.
An efficient two-phase interactive solution procedure and an exploratory solution procedure are developed to obtain a good solution that maximizes the total supply chain profit and the satisfactory degree. The proposed solution procedure, modified from Sakawa et al.’s interactive fuzzy programming approach, can be easily adopted by practitioners. Through a negotiation case study, a well-known network product manufacturing supply chain in Taiwan is presented to demonstrate the effectiveness and aptness of the proposed model and the solution procedure, as compared with Sakawa et al.’s method with only one objective at the manufacturer level.
The results indicate that the interactive and adjusted process between upstream and downstream members in a supply chain is necessary. This can maximize the total supply chain profit and the satisfactory degree. It is extremely important for all members in the supply chain to closely integrate together in order to gain mutual benefits and create their global competitive advantages.
Future research topics might include model formulation of arborescent supply chains, development of new solution procedures, and consideration of fuzzy parameters.
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