臺灣博碩士論文加值系統

現今產業面臨快速移動的競爭市場以及全球化趨勢，為滿足顧客需求與服務水準，企業會將非核心業務的物流作業交給專業的物流公司執行，此專業物流公司稱為第三方物流(Third Party Logistics, 3PL)。然而，傳統第三方物流供應商只提供實體運輸相關的物流作業，對於供應鏈資源無法做一有效的整合管理，此情況下第三方物流已無法滿足顧客要求，因此有了第四方物流(Fourth Party Logistics, 4PL)供應商的產生。第四方物流主要善用資訊與科技來進行供應鏈中資源整合規劃作業及執行，提供顧客有效的供應鏈資源整合解決方案，其中如何將物流工作整合或作業合併指派給適當的第三方物流供應商為一重要議題。在實務中決策者有時面對第四方物流的決策問題必須考慮目標的不同重要性。過去一些研究使用權重型模糊目標規劃來設計不同重要性目標的最佳化問題，然而決定合適的權重對決策者是困難的。本論文主要透過優先型模糊目標規劃建構第四方物流作業指派問題，並提出改良式粒子群優法來求解，本論文所提出之決策方法不需要決定目標的權重值，可避免不當的資源設定使問題無可行解。所提出之改良式粒子群優法主要分別加入擾動及突變運算，並透過數值分析比較演算法績效，研究顯示所提出之具有突變運算的改良式粒子群優法有良好績效，可避免演算法太早落入區域最佳解，並且有效解決本論文之第四方物流指派問題。

Globalization has increased the competition many businesses face. In order to satisfy customer demand and provide high levels of service, enterprises tend to outsource their non-core business, such as logistics operations, to professional logistics service providers. Such services are called 3PL (third-party logistics). However, traditional 3PL providers only offer logistic operations related to physical transportation, and cannot effectively integrate supply chain resources. 3PL can no longer satisfy customer demand under such circumstances, and 4PL (fourth-party logistics) providers have begun to develop. 4PL mainly utilizes information and technology to conduct supply chain resource integration and execution, as well as providing effective supply chain resource integration solutions to customers. One of the key issues is how to assign logistic activities integration or jobs consolidation to appropriate 3PL providers. Previous studies have adopted weighted fuzzy goal programming to design optimization problems. However, it is difficult for decision-makers to determine proper weights. This dissertation constructs activity assignment problem of fourth party logistics by preemptive fuzzy integer goal programming, and proposes a modified particle swarm optimization to solve such problem. The proposed method does not require weights, and precludes results lacking feasible solutions caused by improper resource setting. Proposed modified particle swarm optimization includes perturbation strategy and mutation operator, respectively. Numerical analysis shows that proposed modified particle swarm optimization with mutation operator possesses performs well and effectively solves the 4PL activity assignment problem.

中文摘要 i
ABSTRACT ii
誌 謝 iv
CONTENTS v
LIST of TABLES vii
LIST of FIGURES viii
CHAPTER 1 INTRODUCTION 1
1.1. Research Motivation 1
1.2. Research Objective 3
1.3. Framework and Organization 4
CHAPTER 2 RELEVANT LITERATURE 6
2.1. Logistics Outsourcing 6
2.1.1. 3PL 7
2.1.2. 4PL 8
2.2. Activity Assignment Problem 9
2.3. Preemptive fuzzy goal programming 11
2.4. Particle Swarm Optimizer 13
2.4.1. Apply PPSO in Optimization of Process Parameters 14
2.4.2. Apply PPSO in Supply Chain Network Design 20
CHAPTER 3 MATHEMATICAL FORMULATION FOR PFZOIGP_4PLOAP 26
3.1. Problem Statement 26
3.2. Problem Assumption 28
3.2.1. Notation 28
3.3. Fuzzy Mathematical Model 30
3.4. Crisp Mathematical Model 33
CHAPTER 4 PREEMPTIVE GOAL EVOLUTIONARY ALGORITHM 36
4.1. Solution Representation 36
4.1.1. Update the New Solution 37
4.2. PPSO Algorithm Procedure 39
4.3. Implementation of MPSO 40
4.3.1. Algorithm Procedure Instances 42
4.3.2. MPSO Performance Test 49
4.3.3. Algorithm Complexity Analysis 58
4.4. Effects of Flexible Resource 60
4.4.1. Brief Summary 65
CHAPTER 5 CONCLUSIONS 66
REFERENCES 68
RESUME 74

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