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具時窗限制之車輛途程決策支援系統

The Decision Support Systems of Vehicle Routing Problems with Time Windows

摘要


車輛途程問題其實就是一種最佳化問題,如何在有限資源下追求最小成本並滿足多需求點的路線配置複雜決策。本研究企圖建立一排程決策支援系統,在最早最晚抵達時間之時窗限制下,規劃多場站之貨物路徑及配送數量,希望能藉此求得最少之運送車輛數。本研究建立之系統模式包括最小鄰近法、基因演算法和禁忌搜尋法三演算法,除可求解不同演算法之最少運送車輛數、運送成本與運算時間外,並比較三演算法之求解結果,以提供業者在不同的情境下的選擇。研究中並以某歷史悠久之個案為例,以驗證本系統之可行性。

並列摘要


A Vehicle Routing Problem (VRP) is a complex optimum problem which encompasses a derivation of minimum total cost locating limited vehicles to service several customer demands. In our research we set up the decision support system of Multi-Depot Vehicle Routing Problem with Time Windows. The model base in VRP-DSS includes the Smallest Neighboring Law, Genetic Algorithm and Tabu Search Algorithm. The performances of the three algorithms are compared by the solutions of the optimum vehicle, operating time and transportation cost in this VRP-DSS. Finally we introduce real data from a historic transportation company to demonstrate the validity of this system.

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