Advanced Techniques for Modifying Metaheuristics
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Advanced Techniques for Modifying Metaheuristics
Methods and Applications
Razmjooy, Navid
Elsevier Science & Technology
01/2026
350
Mole
Inglês
9780443329722
15 a 20 dias
Descrição não disponível.
1. Introduction
2. Overview of metaheuristics and their applications
3. Motivation for modifying metaheuristics
4. Aims and objectives of the book
5. Metaheuristic Algorithms and Their Limitations
6. Brief overview of classical metaheuristic algorithms
7. Limitations of classical metaheuristic algorithms
8. Need for modifying metaheuristics
9. Review of Advanced Techniques for Modifying Metaheuristics
10. Review of literature on advanced techniques for modifying metaheuristics
11. Taxonomy of advanced techniques for modifying metaheuristics
12. Comparative analysis of advanced techniques for modifying metaheuristics
13. Evolutionary Algorithm-Based Modifications
14. Overview of evolutionary algorithms
15. Modifications based on population diversity
16. Modifications based on parent selection
17. Modifications based on mutation and crossover operators
18. Experimental evaluation of evolutionary algorithm-based modifications
19. Swarm Intelligence-Based Modifications
20. Overview of swarm intelligence algorithms
21. Modifications based on communication strategies
22. Modifications based on individual behavior
23. Modifications based on collective behavior
24. Experimental evaluation of swarm intelligence-based modifications
25. Hybrid Approaches for Modifying Metaheuristics
26. Overview of hybrid metaheuristics
27. Integration of advanced techniques into hybrid metaheuristics
28. Case studies on hybrid approaches for modifying metaheuristics
29. Applications of Modified Metaheuristics
30. Applications of modified metaheuristics in engineering and design optimization
31. Applications of modified metaheuristics in finance and economics
32. Applications of modified metaheuristics in healthcare and medical diagnosis
33. Applications of modified metaheuristics in social sciences and humanities
34. Empirical Evaluation of Modified Metaheuristics
35. Experimental evaluation frameworks for modified metaheuristics
36. Performance evaluation measures for modified metaheuristics
37. Case studies on empirical evaluation of modified metaheuristics
38. Future Directions and Emerging Trends
39. Emerging trends in modifying metaheuristics
40. Future directions and challenges in modifying metaheuristics
41. Potential applications and impact of modified metaheuristics
2. Overview of metaheuristics and their applications
3. Motivation for modifying metaheuristics
4. Aims and objectives of the book
5. Metaheuristic Algorithms and Their Limitations
6. Brief overview of classical metaheuristic algorithms
7. Limitations of classical metaheuristic algorithms
8. Need for modifying metaheuristics
9. Review of Advanced Techniques for Modifying Metaheuristics
10. Review of literature on advanced techniques for modifying metaheuristics
11. Taxonomy of advanced techniques for modifying metaheuristics
12. Comparative analysis of advanced techniques for modifying metaheuristics
13. Evolutionary Algorithm-Based Modifications
14. Overview of evolutionary algorithms
15. Modifications based on population diversity
16. Modifications based on parent selection
17. Modifications based on mutation and crossover operators
18. Experimental evaluation of evolutionary algorithm-based modifications
19. Swarm Intelligence-Based Modifications
20. Overview of swarm intelligence algorithms
21. Modifications based on communication strategies
22. Modifications based on individual behavior
23. Modifications based on collective behavior
24. Experimental evaluation of swarm intelligence-based modifications
25. Hybrid Approaches for Modifying Metaheuristics
26. Overview of hybrid metaheuristics
27. Integration of advanced techniques into hybrid metaheuristics
28. Case studies on hybrid approaches for modifying metaheuristics
29. Applications of Modified Metaheuristics
30. Applications of modified metaheuristics in engineering and design optimization
31. Applications of modified metaheuristics in finance and economics
32. Applications of modified metaheuristics in healthcare and medical diagnosis
33. Applications of modified metaheuristics in social sciences and humanities
34. Empirical Evaluation of Modified Metaheuristics
35. Experimental evaluation frameworks for modified metaheuristics
36. Performance evaluation measures for modified metaheuristics
37. Case studies on empirical evaluation of modified metaheuristics
38. Future Directions and Emerging Trends
39. Emerging trends in modifying metaheuristics
40. Future directions and challenges in modifying metaheuristics
41. Potential applications and impact of modified metaheuristics
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Metaheuristics; optimization; algorithm modification; performance improvement; Computational Intelligence; taxonomy; evolutionary algorithm; swarm intelligence; hybrid metaheuristics
1. Introduction
2. Overview of metaheuristics and their applications
3. Motivation for modifying metaheuristics
4. Aims and objectives of the book
5. Metaheuristic Algorithms and Their Limitations
6. Brief overview of classical metaheuristic algorithms
7. Limitations of classical metaheuristic algorithms
8. Need for modifying metaheuristics
9. Review of Advanced Techniques for Modifying Metaheuristics
10. Review of literature on advanced techniques for modifying metaheuristics
11. Taxonomy of advanced techniques for modifying metaheuristics
12. Comparative analysis of advanced techniques for modifying metaheuristics
13. Evolutionary Algorithm-Based Modifications
14. Overview of evolutionary algorithms
15. Modifications based on population diversity
16. Modifications based on parent selection
17. Modifications based on mutation and crossover operators
18. Experimental evaluation of evolutionary algorithm-based modifications
19. Swarm Intelligence-Based Modifications
20. Overview of swarm intelligence algorithms
21. Modifications based on communication strategies
22. Modifications based on individual behavior
23. Modifications based on collective behavior
24. Experimental evaluation of swarm intelligence-based modifications
25. Hybrid Approaches for Modifying Metaheuristics
26. Overview of hybrid metaheuristics
27. Integration of advanced techniques into hybrid metaheuristics
28. Case studies on hybrid approaches for modifying metaheuristics
29. Applications of Modified Metaheuristics
30. Applications of modified metaheuristics in engineering and design optimization
31. Applications of modified metaheuristics in finance and economics
32. Applications of modified metaheuristics in healthcare and medical diagnosis
33. Applications of modified metaheuristics in social sciences and humanities
34. Empirical Evaluation of Modified Metaheuristics
35. Experimental evaluation frameworks for modified metaheuristics
36. Performance evaluation measures for modified metaheuristics
37. Case studies on empirical evaluation of modified metaheuristics
38. Future Directions and Emerging Trends
39. Emerging trends in modifying metaheuristics
40. Future directions and challenges in modifying metaheuristics
41. Potential applications and impact of modified metaheuristics
2. Overview of metaheuristics and their applications
3. Motivation for modifying metaheuristics
4. Aims and objectives of the book
5. Metaheuristic Algorithms and Their Limitations
6. Brief overview of classical metaheuristic algorithms
7. Limitations of classical metaheuristic algorithms
8. Need for modifying metaheuristics
9. Review of Advanced Techniques for Modifying Metaheuristics
10. Review of literature on advanced techniques for modifying metaheuristics
11. Taxonomy of advanced techniques for modifying metaheuristics
12. Comparative analysis of advanced techniques for modifying metaheuristics
13. Evolutionary Algorithm-Based Modifications
14. Overview of evolutionary algorithms
15. Modifications based on population diversity
16. Modifications based on parent selection
17. Modifications based on mutation and crossover operators
18. Experimental evaluation of evolutionary algorithm-based modifications
19. Swarm Intelligence-Based Modifications
20. Overview of swarm intelligence algorithms
21. Modifications based on communication strategies
22. Modifications based on individual behavior
23. Modifications based on collective behavior
24. Experimental evaluation of swarm intelligence-based modifications
25. Hybrid Approaches for Modifying Metaheuristics
26. Overview of hybrid metaheuristics
27. Integration of advanced techniques into hybrid metaheuristics
28. Case studies on hybrid approaches for modifying metaheuristics
29. Applications of Modified Metaheuristics
30. Applications of modified metaheuristics in engineering and design optimization
31. Applications of modified metaheuristics in finance and economics
32. Applications of modified metaheuristics in healthcare and medical diagnosis
33. Applications of modified metaheuristics in social sciences and humanities
34. Empirical Evaluation of Modified Metaheuristics
35. Experimental evaluation frameworks for modified metaheuristics
36. Performance evaluation measures for modified metaheuristics
37. Case studies on empirical evaluation of modified metaheuristics
38. Future Directions and Emerging Trends
39. Emerging trends in modifying metaheuristics
40. Future directions and challenges in modifying metaheuristics
41. Potential applications and impact of modified metaheuristics
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
