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Название: Combinatorial Optimization Under Uncertainty: Real-Life Scenarios in Allocation Problems Автор: Ritu Arora, Shalini Arora, Anand J. Kulkarni, Patrick Siarry Издательство: CRC Press Серия: Advances in Metaheuristics Год: 2023 Страниц: 221 Язык: английский Формат: pdf (true) Размер: 13.3 MB
This book discusses the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solutions for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are other factors which affect and augment unpredictability in the market. The intent of this book is to develop mathematical structures for different aspects of allocation problems depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method, Ranking function and Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty include scheduling, cyclic bottleneck assignment problem, bilevel transportation problem, multi-index transportation problem, retrial queuing, uncertain matrix games, optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, intuitionistic fuzzy quadratic programming problem, and multi-objective optimization problem. This book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of this book may further help to explore new avenues leading toward multidisciplinary research discussions.
Combinatorial problems play a significant role in the field of optimization. Distinct mathematical models are developed for different aspects of allocation problems depicting real-life situations. Uncertainty can be seen in every sphere of life. It is an important factor which affects the market in each and every aspect. The global pandemic is another factor due to which uncertainty in the market increase manyfold and thus the market behaviour needs to be examined under such situations. Uncertain parameters can be dealt with via different approaches such as fuzzy programming, grey programming, robust optimization and queues etc. The objective of this edited book is to develop mathematical structures for different aspects of allocation problems depicting real-life situations. The intent is to find optimal, compromise optimal or satisfactory solutions for various allocation problems not only with the existing optimization techniques but also with other novel and modified approaches along with the usage of the software. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method and Ranking function, to name a few. Distinct problems which are incorporated in this book under uncertainty include scheduling, the cyclic bottleneck assignment problem, the bilevel transportation problem, the multi-index transportation problem, retrial queuing, uncertain matrix games, the optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, the intuitionistic fuzzy quadratic programming problem and the multi-objective optimization problem.
The book intends to discuss the basic ideas, underlying principles, mathematical formulations, solutions and analysis and applications of the different combinatorial problems. It may provide guidelines to potential researchers about the choice of such methods for solving a particular class of problems at hand. The contributions of the book may further help to explore new avenues leading toward multidisciplinary research discussions. Every chapter submitted to the book has been critically evaluated by at least two expert reviewers. The critical suggestions by the reviewers helped and influenced the authors of the individual chapters to enrich the quality in terms of experimentation, performance evaluation, representation etc. The book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems.
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Combinatorial Optimization Under Uncertainty: Real-Life Scenarios in Allocation Problems 
Название: Combinatorial Optimization Under Uncertainty: Real-Life Scenarios in Allocation Problems