在人類的活動中，存在著大量決策問題，其中所探討的決策過程、決策工具、決策方法，其目的都是為求取符合需要的最佳解。求解過程所依據的不外乎是經驗的累積與工具的運用。隨著人類活動範圍從局域到廣域，彼此的連結度從鬆散到緊密，所遇到的問題越來越複雜化，以往所依據的經驗與工具，似乎無法較有效率的處理現在所遇到的龐大問題。 學者們從生物群體行為系統中探討其潛在智能，加上計算機技術的快速精進，提出了一系列藉由生物智能觀念的問題求解。而‘粒子群優化演算法’就是生物體經由自身經驗與群體經驗所計算的求解方法，它具有參數設定少、搜尋速度快和可行性高的優點。所以目前已被學者們廣泛發表相關之實務應用。 此論文內容就是藉由‘粒子群優化演算法’的優點應用於企業網路採購時的優化問題求解。希望能提供一種更簡潔、更有效、更優化的參考依據，利於專案執行者於專案決策時，多了一種決策過程中更有效率的決策工具。 In human activities a lot of decision-making issues exist, among them, the decision-making process, tool, and approach, all these need to acquire the best solution to meet their requirements. Inevitably, the solution-seeking process focuses on the experience-accumulation and tool-application. Following the activity scope of human-from narrow to wide; and their mutual link-from loose to tight, the facing problems have become more and more complex. Earlier experiences or tools seem not possible to deal with existing big problem efficiently. Scholars explored the potential intelligence from the system of biological colony behavior, fueled by the fast development of calculator technology, to present a series of solution derived from the biological intelligence concept. However, the particle swarm optimization algorithm (PSO) is a solution formula through the calculation on self experience and colony experiences of creatures. Its merits include few parameters setting, prompt sourcing speed, and high feasibility. Consequently, many scholars had massively announced the related applications in practice. This thesis adopts the merits of PSO to deal with the optimization problem of enterprise’s network procurement, in order to provide references of more simple, effective, and optimal standards. Thereby it offers a more efficient tool for the project-performer in the course of decision making.
