Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques.
This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice.
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Table of Contents
1. Multi-objective combinatorial optimization problems: Social, Keywords, and Journal mapsMehdi Toloo, Siamak Talatahari, Iman Rahimi and Amir H. Gandomi
2. The Fundamentals and Potential of Heuristics and Metaheuristics for Multi-Objective Combinatorial Optimization Problems and Solution Methods
Ana Carolina Borges Monteiro, Reinaldo Padilha Fran?a, Rangel Arthur, Yuzo Iano and Reinaldo Padilha Fran?a
3. A survey on links between multiple objective decision making and data envelopment analysis
Amineh Ghazi and Farhad Hosseinzadeh Lotfi
II. New methods for combinatorial optimization problems
4. Improved Crow Search Algorithm Based on Arithmetic Cross Over- A Novel Metaheuristic Technique for Solving Engineering Optimization Problems
S N Kumar, A Lenin Fred, R. Jonisha Miriam, Padmanabhan Parasuraman, Balazs Gulyas, Ajay Kumar Haridhas and Nisha Dayana
5. MOGROM: Multi-objective Golden Ratio Optimization Algorithm
Behrooz Vahidi, Amin Foroughi and Abolfazl Rahiminejad
III. Application of random-based methods for combinatorial optimization problems
6. Multi-Objective Charged System Search for Optimum Location of Bank Branch
Siamak Talatahari
7. Application of Multi-objective Grey Wolf Optimization in Gasification-based Problems
Siamak Talatahari
8. A VDS-NSGA-II Algorithm for Multi-Year Multi-Objective Dynamic Generation and Transmission Expansion Planning
Ali Esmaeel Nezhad
9. A Multi-Objective Cuckoo Search Algorithm for Community Detection in Social Networks
Farhad Soleimanian Gharehchopogh and Shafih Ghafori
IV. Application of other methods for combinatorial optimization problems
10. Finding efficient solutions of the multi-criteria assignment problem
Emmanuel Kwasi Mensah, Esmaeil Keshavarz and Mehdi Toloo
11. Application of Multi-objective Optimization in Thermal Design and Analysis of Complex Energy Systems
Ali Baghernejad and Elnaz Aslanzadeh
12. A Multi-Objective Nonlinear Combinatorial Model for Improved Planning of Tour Visits Using a Novel Binary Gaining-Sharing knowledge-based Optimization Algorithm
Ali Wagdy wagdy, Said Hassan, Prachi Agrawal and Talari Ganesh
13. Variables Clustering Method to Enable Planning of Large Supply Chains
Emilio Bertolotti Sr
Authors
Mehdi Toloo Department of Business Transformation, Surrey Business School, University of Surrey, Guildford GU2 7XH, United Kingdom.Department of Systems Engineering, Faculty of Economics, Technical University of Ostrava, Ostrava, Czech Republic
Department of Operations Management & Business Statistics, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman. Dr. Mehdi Toloo is a Full Professor in the Faculty of Economics, Technical University of Ostrava, and Faculty of Business
Administration, University of Economics, Prague, Czech Republic. He received his Masters of Science in Applied Mathematics and
his Ph.D. in Operations Research. Dr. Toloo's areas of interest include Operations Research, Decision Analysis, Performance
Evaluation, Multi-Objective Programming, and Mathematical Modelling. He has contributed to numerous international conferences
as a chair, keynote speaker, and member of the scientific committee. He is an area editor for the Elsevier journal Computers and
Industrial Engineering and an associate editor for RAIRO-Operations Research. His publications include the book Introduction to
Scientific Computing: 100 Problems and Solutions in Pascal and papers in top-tier journals such as Applied Mathematics and
Computers, Applied Mathematic Modeling, Expert Systems with Applications, and Computers and Mathematics with Applications. Siamak Talatahari Department of Civil Engineering, University of Tabriz, Tabriz, Iran.
School of Civil and Environment Engineering, University of New South Wales, Sydney, Australia.. Dr. Siamak Talatahari received his Ph.D degree in Structural Engineering from University of Tabriz, Iran. After graduation, he
joined the University of Tabriz where he is presently Professor of Structural Engineering. He is the author of more than 100 papers
published in international journals, 30 papers presented at international conferences and 8 international book chapters. Dr. Talatahari
has been recognized as Distinguished Scientist in the Ministry of Science and Technology and as Distinguished Professor at the
University of Tabriz. He also teaches at the Yakin Dogu University, Nicosia, Cyprus. In addition, he is a co-author with our author
Xin-She Yang of Swarm Intelligence and Bio-Inspired Computation: Structural Optimization Using Krill Herd Algorithm;
Metaheuristics in Water, Geotechnical and Transport Engineering, and Metaheuristic Applications in Structures and
Infrastructures, all published by as Insights by Elsevier. Iman Rahimi University of Technology Sydney, Sydney, Australia.. Iman Rahimi, PhD, is a distinguished research scholar at the University of Technology Sydney, Australia, specializing in machine learning, optimization, and applied mathematics. He holds dual doctorates in Industrial Engineering and Computer Science, along with a BSc and MSc in Applied Mathematics. Dr. Rahimi has authored and edited several influential books, including titles on evolutionary computation and big data analytics, and has contributed extensively to academic literature as a reviewer for high-ranking journals. His editorial experience spans multiple publications, and he has received numerous international awards and research grants, highlighting his significant contributions to the field. With a robust background in operations research, Dr. Rahimi continues to advance knowledge in multiobjective optimization and its applications in various industries.
