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1 Introduction: Best Matching and Best Match |
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1 | (18) |
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1.1 What Is Best Matching? |
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1 | (3) |
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1.2 Definitions and Scope |
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4 | (5) |
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1.2.1 Distributed Systems |
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6 | (2) |
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1.2.2 Collaboration Versus Competition |
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8 | (1) |
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1.3 Best Matching in Practice |
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9 | (3) |
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12 | (7) |
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14 | (5) |
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2 The PRISM Taxonomy of Best Matching |
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19 | (24) |
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19 | (11) |
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2.1.1 D1: Sets of Individuals |
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21 | (1) |
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2.1.2 D2: Matching Conditions |
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22 | (4) |
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2.1.3 D3: Matching Criteria |
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26 | (3) |
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2.1.4 D+: Time or Progression |
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29 | (1) |
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2.1.5 The Prismatic Structure of the PRISM Taxonomy |
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30 | (1) |
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2.2 Four Examples of the PRISM Taxonomy Application |
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30 | (7) |
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2.2.1 Balancing Collaborative Assembly Lines (M : 1/RC, PR, RS/ -- --, WS) |
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30 | (1) |
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2.2.2 Part Pairing for Concurrent Loading-Machining (1:1//-- OS) |
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31 | (2) |
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2.2.3 Dynamic Teaming with Interdependent Preferences (M : 1/RC, IP/ +, OS/DI, ES) |
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33 | (2) |
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2.2.4 Location-Allocation Decisions in CNO (1: M: M/RC, PR, RS/ + --, WS) |
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35 | (2) |
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37 | (6) |
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41 | (2) |
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3 Mathematical Models of Best Matching |
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43 | (20) |
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3.1 Why Mathematical Modeling for Best Matching? |
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43 | (2) |
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45 | (4) |
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3.2.1 One-to-One Matching |
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46 | (1) |
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3.2.2 Generalized Matching |
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47 | (1) |
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3.2.3 Multi-Dimensional Matching |
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48 | (1) |
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49 | (8) |
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3.3.1 Resource-Constrained Matching |
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49 | (2) |
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3.3.2 Matching with Precedence Relations |
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51 | (1) |
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3.3.3 Matching with Resource Sharing |
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51 | (2) |
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3.3.4 Matching with Interdependent Preferences |
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53 | (3) |
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56 | (1) |
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57 | (2) |
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3.5 D+. Static Versus Dynamic Matching |
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59 | (1) |
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60 | (3) |
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62 | (1) |
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4 Distributed Decision-Making and Best Matching |
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63 | (18) |
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4.1 Single Versus Multiple Decision-Makers |
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63 | (2) |
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4.2 Distribution of Decisional Abilities |
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65 | (9) |
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4.2.1 Example 1: Intelligent Warehouse Management Systems |
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68 | (2) |
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4.2.2 Example 2: Precision Agriculture |
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70 | (2) |
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4.2.3 Alternative Configurations---Advantages and Limitations |
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72 | (2) |
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4.3 Nature of Interactions |
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74 | (2) |
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76 | (5) |
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78 | (3) |
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5 Static and Centralized Matching |
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81 | (44) |
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5.1 Motivation for Using Algorithms |
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81 | (2) |
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5.2 Heuristics and Exact Algorithms |
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83 | (19) |
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83 | (3) |
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5.2.2 Deferred Acceptance Algorithm |
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86 | (3) |
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5.2.3 Lagrangian Relaxation Method |
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89 | (9) |
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5.2.4 Branch-and-Bound Method |
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98 | (4) |
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102 | (16) |
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5.3.1 Genetic Algorithm (GA) |
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103 | (4) |
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5.3.2 Greedy Randomized Adaptive Search Procedure (GRASP) |
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107 | (3) |
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5.3.3 Ant Colony Optimization (ACO) |
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110 | (4) |
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114 | (4) |
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118 | (7) |
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122 | (3) |
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6 Dynamic and Distributed Matching |
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125 | (42) |
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6.1 Why Are Static and Centralized Algorithms not Always Sufficient? |
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125 | (2) |
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6.2 Real-Time Optimization |
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127 | (15) |
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6.2.1 Periodic Review Method |
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129 | (5) |
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6.2.2 Continuous Review Method |
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134 | (8) |
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142 | (11) |
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6.3.1 Multi-agent Systems |
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142 | (4) |
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6.3.2 Interaction Protocols |
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146 | (7) |
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6.4 The "AI" Challenges (Artificial Intelligence; Analytics and Informatics) |
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153 | (6) |
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6.4.1 Artificial Intelligence |
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153 | (4) |
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6.4.2 Analytics and Informatics |
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157 | (2) |
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159 | (8) |
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163 | (4) |
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7 Extended Examples of Best Matching |
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167 | (54) |
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7.1 Understanding Through Analogy |
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167 | (3) |
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7.2 E1: Collaborative Supply Networks (M: 1/RC, RS/--, OS/DI) |
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170 | (12) |
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7.2.1 Mathematical Formulation |
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172 | (2) |
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7.2.2 D+: Task Administration Protocol |
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174 | (5) |
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179 | (1) |
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180 | (2) |
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7.3 E2: Collaborative Assembly Lines (M: 1/RC, PR, RS/-- -- --, GP/DI) |
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182 | (12) |
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7.3.1 Mathematical Formulation |
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184 | (4) |
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7.3.2 D+: Collaborative Multi-agent System |
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188 | (4) |
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192 | (1) |
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192 | (2) |
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7.4 E3: Clustering with Interdependent Preferences (M: 1/RC, IP/ +, OS/ES) |
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194 | (8) |
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7.4.1 Optimal Clustering: Genetic Algorithm (GA) |
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196 | (3) |
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7.4.2 D+: Association/Dissociation |
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199 | (2) |
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201 | (1) |
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201 | (1) |
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7.5 E4: Collaborative Service Enterprises (1:M:M/RC, RS/ + --, WS) |
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202 | (9) |
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7.5.1 Mathematical Formulation |
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204 | (2) |
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7.5.2 Optimization: Tabu Search |
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206 | (4) |
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210 | (1) |
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211 | (10) |
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213 | (4) |
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217 | (4) |
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8 Frontiers in Best Matching |
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221 | (8) |
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8.1 Emerging Technologies Dealing with Best Matching |
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221 | (2) |
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222 | (1) |
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8.1.2 Cloud Manufacturing |
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222 | (1) |
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8.2 Technical Challenges of Best Matching |
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223 | (3) |
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8.2.1 Efficient Computation and Communication |
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223 | (1) |
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8.2.2 Conflict and Error Detection and Prevention |
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224 | (1) |
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8.2.3 Incentives for Collaboration |
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224 | (1) |
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8.2.4 Data Availability and Reliability |
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225 | (1) |
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226 | (3) |
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228 | (1) |
Index |
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229 | |