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This
is a valuable reference to practitioners, students and researchers in the area of optimization methods. CI is investigated by solving discrete variable truss structural problems, mixed variable design engineering problems, linear and nonlinear constrained test problems and real-world applications from the manufacturing domain.
Inhaltsverzeichnis
Chapter 1: Introduction to Metaheuristic Algorithms
Chapter 2: Literature Survey on Nature Inspired Optimisation Methodologies and Constraint Handling
Chapter 3: Cohort Intelligence (CI) Using the Static Penalty Function (SPF) Approach
Chapter 4: Constraint Handling Using the Self-Adaptive Penalty Function (SAPF) Approach
Chapter 5: Hybridization of Cohort Intelligence with Colliding Bodies Optimisation
Chapter 6: Validation of CI-SPF, CI-SAPF and CI-SAPF-CBO for Solving Discrete/Integer and Mixed Variable Problems
Chapter 7: Solution to Real-World Applications
Chapter 8: Conclusions and Recommendations
Appendix: Problem Statements for the Truss Structure, Design Engineering, Linear and Nonlinear Programming and Manufacturing Problems
Index
Über den Autor / die Autorin
Ishaan R. Kale is a researcher for the Optimization and Agent Technology Research (OAT Research) Lab.
Anand J. Kulkarni is an Associate Professor at the Institute of Artificial Intelligence, MIT World Peace University, India.
Zusammenfassung
This is a valuable reference to practitioners, students and researchers in the area of optimization methods. CI is investigated by solving discrete variable truss structural problems, mixed variable design engineering problems, linear and nonlinear constrained test problems and real-world applications from the manufacturing domain.
