标题: | 一般化卡车拖车路线问题 Generalized Truck and Trailer Routing Problem |
作者: | 吴志仁 Chih-Jen Wu 韩复华 Anthony Fu-Wha Han 运输与物流管理学系 |
关键字: | 车辆路线问题;卡车与拖车路线问题;包容性深广度搜寻;限制规划;Vehicle Routing Problem (VRP);Truck and Trailer Routing Problem (TTRP);Generalized Intensification and Diversification Search (GIDS);Constraint Programming (CP) |
公开日期: | 2002 |
摘要: | 摘 要 卡车与拖车路线问题(Truck and Trailer Routing Problem, TTRP)是传统车辆路线问题(Vehicle Routing Problem, VRP)的一种衍生型态,藉由卡车或整车(卡车附挂拖车)之路线服务具有不同可及性的顾客。本研究依TTRP问题特性,从合理化构建成本与扩充限制条件两方面着手,使其成为“一般化卡车拖车路线问题”(Generalized TTRP, GTTRP),更能符合实际应用的需求。GTTRP考虑的物流配送较VRP与TTRP更具实用弹性,但另一方面问题的复杂性也更高。 本研究使用“限制规划”(Constraint Programming, CP)与“包容性深广度搜寻法”(Generic Intensification and Diversification Search, GIDS),发展适合GTTRP的求解工具。CP应用于起始解构建部分。GIDS巨集启发式方法则搭配门槛接受法(Threshold Accepting, TA)与大洪水法(Great Deluge Algorithm, GDA)两种搜寻法,以及两极跳跃法(Flip Flop, FF)构建多组演算模组进行路线改善测试。本研究依据Chao的TTRP题库,建立一组18题的GTTRP测试题库,并以C++语言撰写程式在AMD PC上执行测试。结果发现,本研究所设计求解GTTRP之模组皆有不错之解题绩效。本研究亦以GTTRP之模式求解TTRP问题,亦发现有5题结果较Chao佳,整体平均误差为4.18%,平均执行时间为15.08秒,比Chao 60747.57秒快了4000倍以上,此亦印证本研究GTTRP求解方法的效果。 ABSTRACT The Truck and Trailer Routing Problem (TTRP) is a variant of traditional Vehicle Routing Problem (VRP). The problem considers the use of trucks as well as the combination of truck-and-trailers to service customers. TTRP is relative new in literature, e.g., Gerdessen (1996) and Chao (2002). This research extends the TTRP to include more generalized considerations, and defines the generalized Truck and Trailer Problem (GTTRP). As contrast to TTRP, which ignores the costs associated with the decoupling / coupling of the truck and the trailer as well as that of additional parking lots to park the trailers, our proposed GTTRP includes such costs in general. We applied Constraint Programming (CP) and the meta-heuristic method of Generalized Intensification and Diversification Search (GIDS) to develop heuristic solution algorithms to solve GTTRP. The initial solution of GTTRP is generated by CP. The GIDS integrates the use of Threshold Accept (TA) and Great Deluge Algorithm (GDA) and Flip Flop (FF) to improve the incumbent solution. For numerical-analysis purposes, we developed a bank of 18 test problems of GTTRP based on Chao’s test problems of TTRP. We wrote computer programs in C++ and implemented our models on an AMD personal computer. Results found that our proposed models can provide useful tools for GTTRP applications. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#NT910423025 http://hdl.handle.net/11536/70337 |
显示于类别: | Thesis |