導引式區域搜尋法(Guided Local Search, GLS)是一種新近發展的巨集啟發式方法，已被應用於求解TSP、VRPTW及VRPBTW等高複雜度的組合最佳化問題上。本研究提出GLS方法應用於車輛路線問題(Vehicle Routing Problem, VRP)之求解架構，並修改GLS的懲罰值設定方式。經由32個VRP標竿例題的測試，結果發現:本研究設定之懲罰值對GLS法的解題績效皆優於原始的懲罰值；平均誤差百分比可達3.70%，證實GLS法具有不錯的VRP解題能力。 The Guided Local Search (GLS), which has been applied to solve several complicated combinatorial optimization problems, such as TSP, VRPTW and VRPBTW, is a new-developed meta-heuristic approach. This research aims to propose a GLS scheme for solving the V
