建立供應鏈的核心競爭力是企業非常重視的議題,其中供應商評選則扮演著關鍵角色,合適的供應商將明顯地降低生產之成本與提升顧客服務水準。因此本文研究一個考量組裝次序規劃、生產線平衡與供應商風險之不確定性的供應商評選問題,並在評選準則中的運輸時間加入時窗限制,強調組裝中心如期生產的重要性,避免顧客的交貨日期延遲。為解決此供應商評選問題,本研究發展出一個穩健最佳化模式,來處理在多階供應鏈中具有供應商風險不確定性之供應商評選問題。此外,本研究也提出一種整合型基因演算法來求解穩健最佳化模式,為了驗證其求解之績效,本研究提出之演算法與另外兩個已知且目前較佳的演算法作案例實證有效性之比較。最後,提出穩健代價作分析,藉此可以探討保護程度與穩健代價之間的關係。另外,將穩健最佳化模式與確定性評選模式之結果作探究,提供決策者決定是否執行穩健規劃之必要性。
Establishing central competitiveness of supply chain is an issue strongly emphasized by enterprises. Among them, the supplier selection plays a key role. The suitable supplier will noticeably the reduce cost of production and promote Level of customer service. Therefore, this thesis studies the supplier selection problem with considering the assembly sequence planning, assembly line balancing problem, uncertainty of supplier risk, and also at transportation time of evaluation criterion to join time window constraints. The importance emphasized to assemble center to produce as scheduled, besides avoid delaying the customer's date of delivery. This research develops a robust optimization mode, in order to solve the uncertainty of supplier risk of supplier selection problem in multi-stage supply chains. In addition, this text also puts forth the integration genetic algorithm to solve robust optimization mode. For identifying it solves of performance, these researches proposed of the algorithm have been already known with other two and better algorithm does the comparison of case substantial evidence usefulness currently. In the end, put forth the robust price analyzes. With this the study protective level and robust price both of relation. Besides, the result of robust optimization mode and determinism mode compares an investigation. Provide if the decision maker decision carries out the necessity of robust plan.
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