Format:
1 Online-Ressource (211 Seiten)
ISBN:
9781000432916
Note:
Description based on publisher supplied metadata and other sources
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Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- Author Bios -- CHAPTER 1: Introduction -- 1.1. APPLICATIONS OF NODE DEPLOYMENT PROBLEM -- 1.1.1. Unmanned Systems -- 1.1.2. Wireless Sensor Networks -- 1.1.3. Healthcare -- 1.1.4. Public Sectors -- 1.1.5. Railway Network Design -- 1.1.6. Distributed Simulation Systems -- 1.2. FUNDAMENTAL ISSUES OF NODE DEPLOYMENT PROBLEM -- 1.2.1. Task -- 1.2.2. Node -- 1.2.3. Environment -- 1.3. RESEARCH PROGRESS OF NODE DEPLOYMENT MODELING -- 1.3.1. Deployment Space -- 1.3.1.1. Candidate Locations -- 1.3.1.2. Deployment Formation -- 1.3.2. Constraints -- 1.3.3. Objective Functions -- 1.3.3.1. Node Deployment in Wireless Sensor Networks -- 1.3.3.2. Node Deployment in Air Defense -- 1.3.3.3. Other Types of Optimization Objective -- 1.4. RESEARCH PROGRESS OF NODE DEPLOYMENT METHODS -- 1.4.1. Encoding -- 1.4.2. Constraints Handling -- 1.4.3. Multi-Objective Handling -- 1.4.4. Algorithms -- 1.4.4.1. Exact Algorithm -- 1.4.4.2. Metaheuristic Algorithm -- 1.5. MAIN ISSUES AND CHALLENGES -- 1.6. BOOK OUTLINE -- CHAPTER 2: Stochastic Node Deployment for Area Coverage Problem -- 2.1. INTRODUCTION -- 2.2. PROBLEM FORMULATION -- 2.2.1. Detection Models -- 2.2.1.1. Binary Detection Model -- 2.2.1.2. Probabilistic Detection Model -- 2.2.2. Network Model -- 2.2.3. Problem Statement -- 2.2.4. NP-Hardness Proof -- 2.3. SOLUTION ALGORITHMS -- 2.3.1. D-VFCPSO -- 2.3.2. Other PSO-Based Algorithm for Area Coverage Problem -- 2.3.3. Complexity Analysis -- 2.4. EXPERIMENTS AND DISCUSSION -- 2.4.1. Test Instances -- 2.4.2. Parameter Setting -- 2.4.3. Analysis of Results -- 2.5. CONCLUSION -- CHAPTER 3: Stochastic Dynamic Node Deployment for Target Coverage Problem -- 3.1. INTRODUCTION -- 3.2. PROBLEM FORMULATION -- 3.2.1. Mathematical Model -- 3.2.2. Scenario-Based Model Reformulation
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3.3. SOLUTION ALGORITHMS -- 3.3.1. NSGA-II -- 3.3.2. MOPSO -- 3.3.2.1. Personal Best Selection -- 3.3.2.2. Non-Dominated Solutions Maintaining and Global Best Selection -- 3.3.2.3. Diversity Maintaining -- 3.3.3. Complexity Analysis -- 3.4. EXPERIMENTS AND DISCUSSION -- 3.4.1. Test Instances -- 3.4.2. Performance Metrics -- 3.4.3. Parameter Turning -- 3.4.4. Analysis of Results -- 3.5. CONCLUSION -- CHAPTER 4: Robust Node Deployment for Cooperative Coverage Problem -- 4.1. INTRODUCTION -- 4.2. PROBLEM FORMULATION -- 4.2.1. The Deterministic and Uncertain Two-Level Cooperative Set Covering Problem -- 4.2.1.1. Two-Level Cooperative Set Covering Problem -- 4.2.1.2. Generalized Uncertain Two-Level Cooperative Set Covering Problem -- 4.2.2. Modeling the Robust Uncertain Two-Level Cooperative Set Covering Problem -- 4.2.2.1. Compact Formulation of the RUTLCSCP -- 4.3. SOLUTION ALGORITHMS -- 4.3.1. Dealing with Subproblem -- 4.3.2. Rule-Based Heuristic for RUTLCSCP -- 4.3.2.1. Processing Procedure -- 4.3.2.2. Complexity Analysis of MRBCH-k -- 4.3.3. Proposed SaDE for RUTLCSCP -- 4.3.3.1. Encoding -- 4.3.3.2. Constraints Handling -- 4.3.3.3. Complexity Analysis of SaDE -- 4.4. EXPERIMENTS AND DISCUSSION -- 4.4.1. Test Instances -- 4.4.2. Analysis of Results -- 4.4.2.1. Solving RUTLCSCP-LA-RC through CPLEX -- 4.4.2.2. Comparisons of MRBCH-k with Different k -- 4.4.2.3. Comparisons of SaDE and Its Variants -- 4.4.2.4. Comparisons on RUTLCSCP -- 4.5. CONCLUSION -- CHAPTER 5: Fuzzy Node Deployment for Cooperative Coverage Problem -- 5.1. INTRODUCTION -- 5.2. PROBLEM FORMULATION -- 5.2.1. Fuzzy Conditional Value-at-Risk -- 5.2.2. Mathematical Model -- 5.2.3. Some Properties on CVaR-FTLCNDP -- 5.2.4. Linear Approximation of CVaR-FTLCNDP -- 5.3. SOLUTION ALGORITHMS -- 5.3.1. Fuzzy Simulation
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5.3.2. Improved Decomposition-Based Multi-Objective Evolutionary Algorithms -- 5.3.2.1. Encoding -- 5.3.2.2. Updating of Individuals -- 5.3.2.3. Complexity Analysis -- 5.4. EXPERIMENTS AND DISCUSSION -- 5.4.1. Performance Metrics -- 5.4.2. Analysis of Results -- 5.4.2.1. Case Study 1 -- 5.4.2.2. Case Study 2 -- 5.5. CONCLUSION -- CHAPTER 6: Simulation-Based Evaluation Analysis of Node Deployment under Risk Preference -- 6.1. INTRODUCTION -- 6.2. SIMULATION-BASED EVALUATION ANALYSIS OF WORST-CASE CVAR NODE DEPLOYMENT -- 6.2.1. Uncertain Initial Position of Penetration Paths -- 6.2.2. Penetration Paths under Uncertainty -- 6.2.3. Scenario-Based Simulation -- 6.2.4. Evaluation Model with Decision Makers' Risk Preference -- 6.3. EXPERIMENTS AND DISCUSSION -- 6.3.1. Case Study 1: Deployment of Sensor Nodes -- 6.3.2. Case Study 2: Deployment of Weapon Nodes -- 6.3.3. Case Study 3: Cooperative Deployment of Sensor and Weapon Nodes -- 6.4. CONCLUSION -- CHAPTER 7: Overview and Future Directions -- Bibliography -- Index
Additional Edition:
Erscheint auch als Druck-Ausgabe Ding, Shuxin Metaheuristics for Resource Deployment under Uncertainty in Complex Systems Milton : Taylor & Francis Group,c2021 ISBN 9781032065205
Language:
English
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