博碩士論文 101426031 完整後設資料紀錄

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DC.contributor工業管理研究所zh_TW
DC.creator江承璋zh_TW
DC.creatorCheng-Chang Chiangen_US
dc.date.accessioned2014-7-28T07:39:07Z
dc.date.available2014-7-28T07:39:07Z
dc.date.issued2014
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=101426031
dc.contributor.department工業管理研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract這篇論文主要探討是應用行產生法求解考量交通壅塞時間與軟時間窗格之車輛途程問題,在這問題中當車輛無法在各顧客特定時間窗格內服務顧客即會產生一懲罰成本加入目標式,並在特定的時間區間產生交通壅塞的尖峰時段,以上兩種性質都增加了求解可行解的困難度,在解法上我們利用行產生法的求解模式進行求解並利用動態規劃對子問題進行求解,在線性規劃中"行"用來表示路徑,並建立一子問題用來產生新的路徑進一步求出可行路徑及最佳解再利用狀態空間鬆弛法來求解,最後我們利用Solomom的例題進行測試。zh_TW
dc.description.abstractThis paper discusses a column generation for the Vehicle Routing Problem subject to soft time window restriction. In this problem, earliness or lateness is allowed although a penalty is incurred and added to solution cost whenever a vehicle serves a customer outside of his time window, and generate traffic congestion within a specific time. Both of them increase the complications of the problem and hard to find feasible solution. We present a column generation algorithm which is the exact optimization algorithm for this problem and then the branch and price help us optimization the result. In the linear programming column represents the route, and construct subproblem to generate new route for improve the answer and use state-space relaxation for dynamic programs to solve it and then we calculate different size of hard time windows problem that is from “Solomon benchmark problems”. en_US
DC.subject車輛途程問題zh_TW
DC.subject軟時間窗格zh_TW
DC.subject交通壅塞時間zh_TW
DC.subject行產生法zh_TW
DC.subjectVehicle routing problemen_US
DC.subjectSoft time windowen_US
DC.subjectTraffic congestionen_US
DC.subjectColumn generationen_US
DC.title應用行產生法求解考量交通壅塞時間與 軟時間窗格之車輛途程問題zh_TW
dc.language.isozh-TWzh-TW
DC.titleUsing Column Generation to Solve the Vehicle Routing Problem with Soft Time Window and Traffic Congestion Timeen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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