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Cohort Intelligence: A Socio-inspired Optimization Method (Hardcover, 1st ed. 2017): Anand Jayant Kulkarni, Ganesh Krishnasamy,... Cohort Intelligence: A Socio-inspired Optimization Method (Hardcover, 1st ed. 2017)
Anand Jayant Kulkarni, Ganesh Krishnasamy, Ajith Abraham
R3,602 Discovery Miles 36 020 Ships in 10 - 15 working days

This Volume discusses the underlying principles and analysis of the different concepts associated with an emerging socio-inspired optimization tool referred to as Cohort Intelligence (CI). CI algorithms have been coded in Matlab and are freely available from the link provided inside the book. The book demonstrates the ability of CI methodology for solving combinatorial problems such as Traveling Salesman Problem and Knapsack Problem in addition to real world applications from the healthcare, inventory, supply chain optimization and Cross-Border transportation. The inherent ability of handling constraints based on probability distribution is also revealed and proved using these problems.

Constraint Handling in Metaheuristics and Applications (Paperback, 1st ed. 2021): Anand J. Kulkarni, Efren Mezura-Montes, Yong... Constraint Handling in Metaheuristics and Applications (Paperback, 1st ed. 2021)
Anand J. Kulkarni, Efren Mezura-Montes, Yong Wang, Amir H Gandomi, Ganesh Krishnasamy
R4,756 Discovery Miles 47 560 Ships in 10 - 15 working days

This book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques. These techniques may be incorporated in suitable metaheuristics providing a solid optimized solution to the problems and applications being addressed. The book comprises original contributions with an aim to develop and discuss generalized constraint handling approaches/techniques for the metaheuristics and/or the applications being addressed. A variety of novel as well as modified and hybridized techniques have been discussed in the book. The conceptual as well as the mathematical level in all the chapters is well within the grasp of the scientists as well as the undergraduate and graduate students from the engineering and computer science streams. The reader is encouraged to have basic knowledge of probability and mathematical analysis and optimization. The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena.

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