臺灣博碩士論文加值系統

城市物流隨著經濟快速發展而逐漸繁盛，又因新冠疫情的肆虐，改變顧客的傳統消費模式，進一步促進電子商務的崛起。然而，物流業的快速發展也帶來污染問題，因此減少運輸過程中的碳排放視為本研究探討之議題。本研究採用異質車輛，並以多艙種(Multi-Compartment)、多趟次(Multi-Trip)之條件進行配送，且具有軟時窗限制，即允許延遲送達，以應對實際運輸過程中的不確定性及變動；同時，考量燃油消耗成本。綜合上述問題特性，構建最佳化數學模型，透過作業研究最佳化軟體於小規模試驗範例驗證其正確性。本研究主要目標為最小化車輛固定成本，次要目標為減少因延遲送達而導致的懲罰成本及燃油消耗成本，從而設計最佳配送路徑。為解決大規模且複雜的車輛途程問題，開發適應性遺傳演算法(Adaptive genetic algorithm, AGA)於實際案例。最終，藉由敏感度分析評估不同參數對模型結果的影響，以及提供改善策略作為決策者的參考框架。

Urban logistics have thrived amidst rapid economic growth, while concurrently being influenced by the COVID-19 pandemic, altering traditional consumer behaviors and boosting e-commerce. However, this rapid expansion in the logistics industry has also heightened environmental concerns, leading this study to focus on reducing carbon emissions during transportation. Using heterogeneous vehicles, the study investigates multi-compartment, multi-trip deliveries within soft time windows constraints, accommodating delays. Fuel consumption costs are considered. Constructing an optimization mathematical model and validating it with small-scale pilot studies using operational research software. The primary goal is to minimize vehicle fixed costs, with secondary aims of reducing penalties from delayed deliveries and optimizing fuel consumption to design efficient delivery routes. Addressing large-scale and complex vehicle routing challenges, an Adaptive Genetic Algorithm (AGA) is developed and validated in practical scenarios. Finally, sensitivity analysis assesses parameter impacts and proposes enhancement strategies for decision-makers.

摘要...i
Abstract...ii
誌 謝...iii
目錄...iv
表目錄...vi
圖目錄...viii
第一章 緒論...1
1.1研究背景與動機...1
1.2研究目的...3
1.3論文架構...3
第二章 文獻探討...5
2.1城市物流(City Logistics)...5
2.2具時窗限制及多趟次車輛途程問題...6
2.3多艙種車輛途程問題...7
2.4異質車輛途程問題...8
2.5油耗相關車輛途程問題...10
2.6適應性遺傳...11
第三章 問題定義...16
3.1車輛途程問題之相關定義...16
3.2數學模型符號描述...17
3.3建構數學模型之目標函數及限制式...19
3.4運用最佳化軟體進行問題之試驗...22
第四章 演算法設計...30
4.1適應性遺傳演算法...31
4.2演算法最佳參數設置...40
第五章 案例探討...46
5.1案例之基本資訊...46
5.2適應性遺傳演算法之配送求解結果...55
5.3參數敏感度測試與分析...58
第六章 結論及建議...63
6.1結論...63
6.2建議...64
參考文獻...65
附錄A...71
附錄B...78
Extended Abstract...85

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