查詢結果分析
來源資料
相關文獻
- MAX-MIN螞蟻演算法於配送中心選址之研究
- Distributed Broadcasting Algorithms in Rotator Graphs
- Machining Parameters Selection for Stock Removal Turning in Process Plans Using a Float Encoding Genetic Algorithm
- A Modified Multistart Method for Multimodal Optimization
- 線性軸幅路網接駁系統最適整合區位、路線與排班模式之研究
- Bayesian Estimation for the Optimum in Single Factor Quadratic Regression
- 衛星探空資料(SATEM)在中央氣象局有限區域預報系統之客觀分析模組的應用
- 二次元靜態連續體結構之最佳化:應用族群概念之基因演算法
- Optimization of Order-packing Travel Route in a Finished Goods Warehouse
- 田口法應用於最佳化設計問題
頁籤選單縮合
題名 | MAX-MIN螞蟻演算法於配送中心選址之研究=The Study of Distribution Center Location Selection Based on MAX-MIN Ant Algorithm |
---|---|
作者姓名(中文) | 徐嘉吟; 黃士滔; | 書刊名 | 品質學報 |
卷期 | 17:1 2010.02[民99.02] |
頁次 | 頁89-97 |
分類號 | 496.8 |
關鍵詞 | MAX-MIN螞蟻演算法; 最佳化; 配送中心; MAX-MIN ant algorithm; Optimization; Distribution center; DC; |
語文 | 中文(Chinese) |
中文摘要 | 摘 要 由於連鎖商店的蓬勃發展,使得顧客對於商品運送服務的要求更為重視,也由於電子商 務的興起,物流業者面臨了極大的衝擊與挑戰,為有效提升經營績效與降低系統總成本,因 此配送中心的選址是物流產業系統成功的關鍵,而配送中心選址與配送路徑的規劃對於顧客 的滿意度以及經營的總成本均有相當大的影響。 本研究以配送中心選址為例,將各個配送點的位置設為已知,編寫成數學模式來求解, 在求解的過程中使用MATLAB 7.0 的軟體編寫模擬程式,使用相較於傳統的蟻群演算法有更 高穩定性的MAX-MIN 螞蟻演算法,並使用費洛蒙自動調整更新概念,根據配送總成本最低 原則對各已知配送點與候選配送中心進行模擬,選擇出適合的配送中心,研究結果顯示此模 式相較於傳統蟻群演算法更適用於較大規模與複雜的配送中心選址問題。 |
英文摘要 | Abstract Since chain store is prosperously developed, customers have higher requirements for merchandise delivery service. With emerging of e-commerce, logistics providers face unprecedented challenges. To effectively increase operational performance and decrease total system cost, selection of distribution center location plays a key role of successful logistics industry system. However selection of distribution center location and delivery routes planning exert considerable influence on customer satisfaction and total operational cost. This article takes selection of distribution center location as example to assume that destinations are given and solves the mathematical model with MATLAB 7.0. By utilizing MATLAB 7.0 to compile simulation formula and use a refined MAX-MIN ant algorithm which is more stable than traditional Ant Colony System (ACS) to select the appropriate location with the pheromone update concept and lowest delivery cost principle for optimization. The result shows that the refined MAX-MIN ant algorithm which is suitable for selective problems for larger and more complex distribution center location than traditional method. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。