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dc.contributor.author呂泓儒en_US
dc.contributor.authorLu, Hong-Ruen_US
dc.contributor.author韓復華en_US
dc.date.accessioned2014-12-12T01:31:29Z-
dc.date.available2014-12-12T01:31:29Z-
dc.date.issued2008en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079632508en_US
dc.identifier.urihttp://hdl.handle.net/11536/42821-
dc.description.abstract回程取貨車輛路線問題(vehicle routing problem with backhauls, VRPB) 是車輛路線問題 (vehicle routing problem, VRP) 的延伸,屬於解題複雜度高的NP-hard問題。其假設車輛必須先服務完所有送貨點顧客,之後利用回程的空車再開始服務取貨點顧客。此類型問題在相關產業的物流配送上應具有相當價值。 可回溯式門檻接受法(Backtracking Adaptive Threshold Accepting, BATA)是由Tarantilis et al. (2001) 首先提出,對於門檻回溯比率值 b 僅考慮b < 1的情形。本研究提出改良型可回溯式門檻接受法(Modified Backtracking Adaptive Threshold Accepting, MBATA),除延用 b > 1 之門檻回溯公式(廖昱傑,2007)以外,另在門檻回溯機制中加入兩極跳躍法(Flip-Flop Method, FF)的概念,其目的即在於當陷入區域最佳解而難以改善時,使其在一個可接受的範圍(門檻值)內進行反向操作的搜尋,如此能增加搜尋機制的廣度。 在求解績效評估方面,本研究以Goetschalckx and Jocabs-Blencha (1989)的62題國際標竿例題進行測試。利用C#語言進行程式撰寫,在Intel(R)雙核心CPU為2.00GHz的個人電腦進行測試。就平均誤差率而言,本研究提出的MBATA比傳統的BATA在所有測試組合中,有15%結果相同,其餘 85% 均有較佳之結果。本研究也對MBATA進行參數測試,並提出建議之參數。最後再與近年來國際期刊之文獻進行比較。本研究62題標竿例題中共有37題找到文獻已知最佳解,而各題最佳結果與已知最佳解平均誤差僅0.16%,平均每題運算時間4.68秒。結果顯示,MBATA在求解VRPB問題上相當具有潛力。zh_TW
dc.description.abstractVehicle Routing Problem with Backhauls (VRPB), an extension of the classical Vehicle Routing Problem, is a very complicated NP-Hard problem. The VRPB assumes that all linehaul customers should be visited before any backhaul customer. Successful applications of the VRPB in real-world distribution will improve the performance of logistics in the related industry. Backtracking Adaptive Threshold Accepting (BATA) was first proposed by Tarantilis et al. (2001), which only considers backtracking factor b < 1. In this paper, we proposed a Modified Backtracking Adaptive Threshold Accepting (MBATA) approach considering the case of b > 1. We also applied the concept of Flip-Flop Method (FF) in backtracking mechanism to enhance the diversification in the search process. The 62 benchmark problems described by Goetschalckx and Jocabs-Blencha (1989) were selected for the evaluation of our meta-heuristics. Our proposed heuristics were coded in Visual C# and tested on a Intel(R) Core(TM)2 CPU 2.00GHz personal computer. We found that our proposed MBATA heuristics outperformed traditional BATA in the average deviation for 85% of all the cases we tested. As compared to the 62 benchmark results reported in recent literatures, we found 37 best-known solutions and the average deviation is merely 0.16%. The average computer time per instance is 4.68 CPU seconds which demonstrated the efficiency and potential applicability of our proposed method.en_US
dc.language.isozh_TWen_US
dc.subject門檻接受法zh_TW
dc.subject可回溯式門檻接受法zh_TW
dc.subject改良型可回溯式門檻接受法zh_TW
dc.subject回程取貨車輛路線問題zh_TW
dc.subject兩極跳躍法zh_TW
dc.subjectThreshold Accepting (TA)en_US
dc.subjectBacktracking Adaptive Threshold Accepting (BATA)en_US
dc.subjectModified Backtracking Adaptive Threshold Accepting (MBATA)en_US
dc.subjectVehicle Routing Problem with Backhauls (VRPB)en_US
dc.subjectFlip-Flop Method (FF)en_US
dc.title以改良型可回溯式門檻接受法求解回程取貨車輛路線問題之研究zh_TW
dc.titleUsing Modified BATA to Solve Vehicle Routing Problem with Backhaulsen_US
dc.typeThesisen_US
dc.contributor.department運輸與物流管理學系zh_TW
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