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Scatter Search: Methodology and Implementations in C

Scatter Search: Methodology and Implementations in C (Paperback, Softcover Repri)

Manuel Laguna, Rafael Marti (지은이)
Kluwer Academic Pub
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Scatter Search: Methodology and Implementations in C
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· 제목 : Scatter Search: Methodology and Implementations in C (Paperback, Softcover Repri) 
· 분류 : 외국도서 > 컴퓨터 > 프로그래밍 > 일반
· ISBN : 9781402073762
· 쪽수 : 291쪽
· 출판일 : 2003-02-28

목차

Foreword. Preface. Acknowledgements. 1: Introduction. 1. Historical Background. 2. Basic Design. 3. C Code Conventions. 2: Tutorial: Unconstrained Nonlinear Optimization. 1. Diversification Generation Method. 2. Improvement Method. 3. Reference Set Update Method. 4. Subset Generation Method. 5. Combination Method. 6. Overall Procedure. 7. Summary of C Functions. 3: Tutorial: 0-1 Knapsack Problems. 1. Diversification Generation Method. 2. Improvement Method. 3. Reference Set Update Method. 4. Subset Generation Method. 5. Combination Method. 6. Overall Procedure. 7. Summary of C Functions. 4: Tutorial: Linear Ordering Problem. 1. The Linear Ordering Problem. 2. Diversification Generation Method. 3. Improvement Method. 4. Reference Set Update Method. 5. Combination Method. 6. Summary of C Functions. 5: Advanced Scatter Search Designs. 1. Reference Set. 2. Subset Generation. 3.Specialized Combination Methods. 4. Diversification Generation. 6: Use of Memory in Scatter Search. 1. Tabu Search. 2. Explicit Memory. 3. Attributive Memory. 7: Connections with Other Population-Based Approaches. 1. Genetic Algorithms. 2. Path Relinking. 3. Intensification and Diversification. 8: Scatter Search Applications. 1. Neural Network Training. 2. Multi-Objective Bus Routing. 3. Arc Crossing Minimization in Graphs. 4. Maximum Clique. 5. Graph Coloring. 6. Periodic Vehicle Loading. 7. Capacitated Multicommodity Network Design. 8. Job-Shop Scheduling. 9. Capacitated Chinese Postman Problem. 10. Vehicle Routing. 11. Binary Mixed Integer Programming. 12. Iterated Re-start Procedures. 13. Parallelization for the P-Median. 14. OptQuest Application. 9: Commercial Scatter Search Implementation. 1. General OCL Design. 2. Constraints and Requirements. 3. OCL Functionality. 4. Computational Experiments. 5. Conclusions. 6. Appendix. 10: Experiences and Future Directions. 1. Experiences and Findings. 2. Multi-Objective Scatter Search. 3. Maximum Diversity Problem. 4. Implications for Future Developments. References. Index.

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