1st Edition

Constraint Handling in Cohort Intelligence Algorithm

By Ishaan R. Kale, Anand J. Kulkarni Copyright 2022
206 Pages 75 B/W Illustrations
by CRC Press

206 Pages 75 B/W Illustrations
by CRC Press

206 Pages 75 B/W Illustrations
by CRC Press

Mechanical Engineering domain problems are generally complex, consisting of different design variables and constraints. These problems may not be solved using gradient-based optimization techniques. The stochastic nature-inspired optimization techniques have been proposed in this book to efficiently handle the complex problems. The nature-inspired algorithms are classified as bio-inspired, swarm,... Read more

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

Biography

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.