A multiple objective approach for green logistics.

近年，可持續發展引起了物流界的關注。要在模糊和不確定的情況對不同資源，服務水平和利潤作出權衡取捨，一個多項目標決策框架是必需的。這份論文，我們會提出一個隨機線性效用涵數的問題。然後發展一個以權衡為基礎的互動方法去解決這個決策問題。這個方法成功地找出穩健的方案和非支配的方案。我們會利用一個北美州聯合運輸路徑選擇的案例來展示此方法的好處。此外，我們會提出一個啟發式解法來增加此互動方法的計算效能。Sustainability is one of many major concerns in the practice of logistics management today. With vague and ambiguous tradeos among resources, service level and prot, a multi-objective decision making framework will be essential. In this work, we formulate the problem using a random linear utility function. We develop a trade-o based interactive method to solve the problem. The interactive method successfully obtains robust solution and non-dominated solutions. We will illustrate the usefulness of the interactive method using an intermodal routing study under NAFTA (North America Free Trade Agreement). In addition, we propose a heuristic solution algorithm for the shortest path routing problem to further improve the efficiency on our interactive method.Detailed summary in vernacular field only.Lee, Ho Cheung Brian.Thesis (M.Phil.)--Chinese University of Hong Kong, 2012.Includes bibliographical references (leaves 123-131).Abstracts also in Chinese.Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Introduction to Multi-objective Decision Making Problem to Green Logistics --- p.3Chapter 1.2 --- Our Contribution --- p.5Chapter 1.3 --- Organization of the thesis --- p.6Chapter 2 --- Literature Review --- p.7Chapter 2.1 --- Routing Problem with Green Consideration --- p.7Chapter 2.1.1 --- Intermodal Routing with Green Considerations --- p.10Chapter 2.2 --- Interactive Routing Method --- p.11Chapter 2.2.1 --- Linear Utility --- p.14Chapter 2.2.2 --- Interactive Routing with Green Consideration --- p.15Chapter 2.3 --- Conclusion --- p.16Chapter 3 --- Methodology --- p.17Chapter 3.1 --- Concept, Notation and Definition --- p.17Chapter 3.1.1 --- Finding Knees in Multi-objective optimization --- p.20Chapter 3.2 --- Existing Interactive Method --- p.23Chapter 3.2.1 --- Framework of interactive routing --- p.23Chapter 3.2.2 --- Geoffrion-Dyer-Feinberg (GDF) Algorithm --- p.24Chapter 3.2.3 --- Reference Direction (RD) Algorithm --- p.29Chapter 3.3 --- Trade-off Compromising Algorithm --- p.35Chapter 3.3.1 --- Description of Trade-off Compromising Algorithm --- p.36Chapter 3.3.2 --- Interactive Method for Multi-objective Shortest Path Problem --- p.45Chapter 3.4 --- Design of Computational Experiments --- p.64Chapter 3.5 --- Conclusion --- p.72Chapter 4 --- Case study on NAFTA --- p.74Chapter 4.1 --- Parameters of the Experiment --- p.77Chapter 4.1.1 --- Cost, Emission and Transit time --- p.77Chapter 4.1.2 --- Scenarios --- p.79Chapter 4.2 --- Computational Result --- p.79Chapter 4.2.1 --- Managerial Implication --- p.86Chapter 4.3 --- Conclusion --- p.97Chapter 5 --- Conclusion --- p.98Chapter A --- Data of the Case study in NAFTA --- p.102Chapter B --- Computational results --- p.106Chapter B.1 --- Computational result of the case studies --- p.106Chapter B.2 --- Computational result of testing number of iterations --- p.121Bibliography --- p.12