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Foreword; Preface; About the Book; Contents; 1 Introduction: Best Matching and Best Match; Abstract; 1.1 What Is Best Matching?; 1.2 Definitions and Scope; 1.2.1 Distributed Systems; 1.2.2 Collaboration Versus Competition; 1.3 Best Matching in Practice; 1.4 Summary; References; 2 The PRISM Taxonomy of Best Matching; Abstract; 2.1 Framework; 2.1.1 D1: Sets of Individuals; 2.1.2 D2: Matching Conditions; 2.1.3 D3: Matching Criteria; 2.1.4 D+: Time or Progression; 2.1.5 The Prismatic Structure of the PRISM Taxonomy; 2.2 Four Examples of the PRISM Taxonomy Application.

1/{\varvec RC}, {\varvec RS}/ --, {\varvec OS}/{\varvec DI}).

2.2.1 Balancing Collaborative Assembly Lines \left({M:1/RC, PR, RS/ --, WS} \right) 2.2.2 Part Pairing for Concurrent Loading-Machining \left({1:1// --, OS} \right) ; 2.2.3 Dynamic Teaming with Interdependent Preferences \left({M:1/RC, IP/ {\, +\, }, OS/DI, ES} \right) ; 2.2.4 Location-Allocation Decisions in CNO \left({1:M:M/RC, PR, RS/ {\, +\, } \, --, WS} \right) ; 2.3 Summary; References; 3 Mathematical Models of Best Matching; Abstract; 3.1 Why Mathematical Modeling for Best Matching?; 3.2 D1. Sets; 3.2.1 One-to-One Matching; 3.2.2 Generalized Matching; 3.2.3 Multi-Dimensional Matching.

3.3 D2. Conditions3.3.1 Resource-Constrained Matching; 3.3.2 Matching with Precedence Relations; 3.3.3 Matching with Resource Sharing; 3.3.4 Matching with Interdependent Preferences; 3.3.4.1 One-to-One Matching with IP; 3.3.4.2 Many-to-One Matching with IP; 3.3.5 Layered Matching; 3.4 D3. Criteria; 3.5 D+. Static Versus Dynamic Matching; 3.6 Summary; References; 4 Distributed Decision-Making and Best Matching; Abstract; 4.1 Single Versus Multiple Decision-Makers; 4.2 Distribution of Decisional Abilities; 4.2.1 Example 1: Intelligent Warehouse Management Systems.

4.2.2 Example 2: Precision Agriculture4.2.3 Alternative Configurations-Advantages and Limitations; 4.3 Nature of Interactions; 4.4 Summary; References; 5 Static and Centralized Matching; Abstract; 5.1 Motivation for Using Algorithms; 5.2 Heuristics and Exact Algorithms; 5.2.1 Hungarian Method; 5.2.2 Deferred Acceptance Algorithm; 5.2.3 Lagrangian Relaxation Method; 5.2.4 Branch-and-Bound Method; 5.3 Metaheuristics; 5.3.1 Genetic Algorithm (GA); 5.3.2 Greedy Randomized Adaptive Search Procedure (GRASP); 5.3.3 Ant Colony Optimization (ACO); 5.3.4 Tabu Search; 5.4 Summary; References.

6 Dynamic and Distributed MatchingAbstract; 6.1 Why Are Static and Centralized Algorithms not Always Sufficient?; 6.2 Real-Time Optimization; 6.2.1 Periodic Review Method; 6.2.2 Continuous Review Method; 6.3 Distributed Control; 6.3.1 Multi-agent Systems; 6.3.2 Interaction Protocols; 6.4 The "AI" Challenges (Artificial Intelligence; Analytics and Informatics); 6.4.1 Artificial Intelligence; 6.4.2 Analytics and Informatics; 6.5 Summary; References; 7 Extended Examples of Best Matching; Abstract; 7.1 Understanding Through Analogy; 7.2 E1: Collaborative Supply Networks ({\varvec M}{:}\

Mismatch or best match? This book demonstrates that best matching of individual entities to each other is essential to ensure smooth conduct and successful competitiveness in any distributed system, natural and artificial. Interactions must be optimized through best matching in planning and scheduling, enterprise network design, transportation and construction planning, recruitment, problem solving, selective assembly, team formation, sensor network design, and more. Fundamentals of best matching in distributed and collaborative systems are explained by providing:? Methodical analysis of various multidimensional best matching processes? Comprehensive taxonomy, comparing different best matching problems and processes? Systematic identification of systems? hierarchy, nature of interactions, and distribution of decision-making and control functions? Practical formulation of solutions based on a library of best matching algorithms and protocols, ready for direct applications and apps development. Designed for both academics and practitioners, oriented to systems engineers and applied operations researchers, diverse types of best matching processes are explained in production, manufacturing, business and service, based on a new reference model developed at Purdue University PRISM Center: "The PRISM Taxonomy of Best Matching". The book concludes with major challenges and guidelines for future basic and applied research in the area of best matching.