應用螞蟻最佳化演算法來改善網通廠棧板堆疊效率之研究

Abstract

在國內外各大網通廠的激烈競爭下，市場上網路設備之競爭已逐漸增大，產品毛利嚴重受到擠壓，企業經營利潤亦隨產品價格競爭顯著降低，故有效控制物流成本已成為企業是否能於激烈競爭之市場上生存的新關鍵利基因素，而如何有效減少出貨棧板的數量，藉以降低運輸費用的成本支出，變成待解決的裝箱問題。 螞蟻最佳化演算法(ant colony optimization, ACO)的優點在於利用一群人工螞蟻(代理人程式)去建構問題的可能解型式，而人工螞蟻遵循費洛蒙痕跡而移動，藉由族群移動與不斷累積並更新費洛蒙，而形成一條選擇的最短路徑。本研究將使用結合螞蟻最佳化與區域搜尋之演算法，針對網通廠出貨棧板上紙箱，採用螞蟻最佳化結合區域搜尋演算法設計一套有效之堆疊系統，搜尋出充分利用空間的堆疊計畫。 本研究根據網通廠的出貨作業特性，針對棧板堆疊作業流程，找出一種可減少出貨棧板數量，藉以降低物流成本的解決方法，透過使用棧板的堆疊最佳化資訊系統，本研究結果顯示網通廠可以減少運送產品時的棧板數量，增加作業人員之人工小時出貨量，降低每一訂單之出貨成本，並擴大倉庫儲存密度與降底每一成品之儲存成本，使網通廠可藉由降低物流成本，獲取產品的價格競爭力。

As the competition dramatically increases in the current network equipment market, the companies, which would like to retain and acquire large marketshare encounter the same issue - the decrease of gross margin. Therefore, cost efficiency is the key when competing in this mature industry. Among all of the cost down strategies, the effective control of logistic cost can normally lead to the big saving in term of processes streamlining. To utilize the capacity of pallet can always result in cost savings since the amount of required pallets will decrease. For this reason, pallet loading is a major problem in network equipment manufacture when it comes to effective logistic control. The advantage of Ant Colony Optimization is using a colony of artificial ant to construct a probable solution. It builds up new solutions with a combination of heuristic information and an artificial pheromone trail. Also, it will use the ACO meta-heuristic with a local search algorithm for solving the pallet loading problem in network equipment manufacturer and developing information system to find out the optimum loading report for operators. This algorithm emphasizes the specific features existed in network equipment manufacture’s shipping operation. Applying this algorithm on the pallet loading operations will provide the solution to minimize the total number of shipping pallet and also utilize the warehouse usage. Hence, having the pallet loading system offer a huge benefit to enterprises in terms of cost saving and ultimately, reach the goal of gross margin increase.