本研究之目的在針對B2B電子商務環境中一個封閉式、多重議題且為一對多的逆向拍賣(Reverse auction)機制，應用分散式雙層規劃(Bi-level distributed programming)同時考量買方和供應商的利益。為上層買方決定分配給各個供應商的採購數量，並為下層供應商制定適當的投標決策，並結合遺傳演算法做為最佳化搜尋工具，期望可以最小化買方的平均單位競標價格或是交付延遲時間。 模型中包含一標單產生模型，供應商會根據買方所指定的交付時間和所分配到的需求數量，利用主生產排程(MPS)和可允諾量(ATP)存貨的資訊來找出一個最小總生產成本的生產計畫並依此計算其單位成本和競標價格；對於供應商決定競標價格以及買方評估供應商群標單方面則是使用模糊理論的模糊決策方法，以便供應商在決定價格時，能夠同時滿足獲利以及合理定價的目標。本研究最後的實驗以驗證研究目的為主，設定不同的實驗參數，以電腦模擬進行實驗並評估本方法之績效。 This study formulates a model, which applies the bi-level distributed programming to solve a sealed-bid, multiple-issue reverse auction problem that can achieve the objectives of buyer and suppliers simultaneously. This model includes a bid construction model. According to the buyer’s demand, Supplier will find out a production plan based on the master production schedule (MPS) and available-to-promise (ATP) inventory that produces the lowest total production cost. This study also employs the max-min decision approach for the decision making of bidding price on supplier side and the evaluation of suppliers’ bid on buyer side. So suppliers can fulfill the objectives of profit and reasonable price when they make the decision of bidding. A genetic algorithm is developed to solve the model. Through the different parameters setting and computer simulation, the purpose of experiments is to evaluate the performance of the proposed approach and verify the research objective.
