Combinatorial Optimization Under Uncertainty : Real-Life Scenarios in Allocation Problems book cover
1st Edition

Combinatorial Optimization Under Uncertainty
Real-Life Scenarios in Allocation Problems

  • Available for pre-order on March 29, 2023. Item will ship after April 19, 2023
ISBN 9781032316581
April 19, 2023 Forthcoming by CRC Press
192 Pages 21 Color & 16 B/W Illustrations

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Book Description

The book intends to discuss the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solution/s for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are another factor which affects and augments unpredictability in the market. The intent of this edited book is to develop mathematical structure for different aspects of allocation problem depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include STAR heuristic approach, Matrix geometric method, Ranking function, Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty includes, 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, healthcare sector, intuitionistic fuzzy quadratic programming problem, multi-objective optimization problem. The book may serve as a valuable reference for the researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of the book may further help to explore new avenues leading toward multidisciplinary research discussions.

Table of Contents

1. Estimation of Uncertainties for Multiserver Queuing Systems with Bernoulli Feedback by Divya Agarwal, Shweta Upadhyay, and Ankita Bansal. 2. Optimality for Fuzzy Transportation Problem under Ranking Method by P Anukokila and B Radhakrishnan. 3. Solution of Bilevel Linear Fractional Transportation Problem with Pythagorean Fuzzy Numbers by Ritu Arora and Shalini Arora. 4. Optimal production evaluation of cotton in different soil and water conditions in Sundarban of West Bengal under hesitant interval fuzzy environment using projection measure by Ankan Bhaumik and Sankar Kumar Roy. 5. A Novel Approach for Feature Detection in Vector Graphics by Karthik Jain, Purvi Gujarathi, Priya Bannur, Pinak Wadilkar and Pradnya V Kulkarni. 6. On Uncertain Matrix Games Involving Linguistic Pythagorean Fuzzy Sets by Deeba R. Naqvi and Geeta Sachdev. 7. Cyclic Surgery Scheduling using Variations of Cohort Intelligence by Mandar S Sapre, Neil Dsouza, Ishaan R Kale, Saksham Agarwal, and Abhishek Phadke. 8. Cone Method for Uncertain Multiobjective Optimization Problems with Minmax Robustness by Ashutosh Upadhayay, Debdas Ghosh, Jauny and Nand Kishor. 9. Solving Multi-Index Transportation Problem with Axial Constraints Having Impaired Flow by Archana Khurana and Veena Adlakha. 10. STAR Heuristic Method: A Novel Approach and its Comparative Analysis with CI Algorithm to solve CBAP in Healthcare by Sharayu Dosalwar, Tanishq Varshney, Ambika Patidar, Rishab Koul, Anand J Kulkarni, Madhura Phatak, and Bhavana Tiple. 11. Development and optimization of quadratic programming problems with intuitionistic fuzzy parameters by Manisha Malik and S. K. Gupta.

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Dr. Ritu Arora received her Ph.D degree from University of Delhi, India. She has a teaching experience of 20 years in University of Delhi. Her research specialization is in the field of mathematical programming and its application to allocation problems. She is currently working as a Professor in the Department of Mathematics, Keshav Mahavidyalaya, University of Delhi.

Prof. Shalini Arora is presently working as Professor in Mathematics at Applied Sciences and Humanities Department, IGDTUW. She has more than 20 years of Teaching experience. She did her Masters and Ph.D in Mathematics from IIT Delhi. She is a recipient of the ‘Young Scientist Award’ by the SERC division of DST. She has a teaching experience of more than 19 years. Her areas of research interest include Mathematical Programming, Allocation Problems viz., Transportation and Assignment Problems, Combinatorial optimization etc.

Dr. Anand J Kulkarni holds a PhD in Distributed Optimization from Nanyang Technological University, Singapore. He worked as Research Fellow at Odette School of Business, University of Windsor, Canada. He is currently working as Professor and Associate Director of the Institute of AI at the MITWPU, Pune, India.

Dr. Patrick Siarry received a PhD degree from the University Paris 6, in 1986 and the Doctorate of Sciences (Habilitation) from the University Paris 11, in 1994. Since 1995, he is working as a professor in automatics and informatics. His main research interests are design of new stochastic global optimization heuristics and their applications to various engineering fields.