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Multi-Objective Combinatorial Optimization Problems and Solution Methods

  • 1st Edition - February 9, 2022
  • Latest edition
  • Editors: Mehdi Toloo, Siamak Talatahari, Iman Rahimi
  • Language: English

Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considere… Read more

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Description

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.

Key features

  • Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications
  • Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature
  • Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms

Readership

Students, educators, and researchers in the field of Data Science, Computer Science, and mathematics. Research scientists and engineers in the fields of operations research, medical and biological sciences, industrial engineers, plant managers as well as research and development scientists

Table of contents

1. Multi-objective combinatorial optimization problems: Social, Keywords, and Journal maps
Mehdi 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 França, Rangel Arthur, Yuzo Iano and Reinaldo Padilha França

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

Product details

  • Edition: 1
  • Latest edition
  • Published: February 15, 2022
  • Language: English

About the editors

MT

Mehdi Toloo

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.
Affiliations and expertise
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

ST

Siamak Talatahari

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.
Affiliations and expertise
Department of Civil Engineering, University of Tabriz, Tabriz, Iran. School of Civil and Environment Engineering, University of New South Wales, Sydney, Australia.

IR

Iman Rahimi

Dr Iman Rahimi is an experienced Machine Learning Engineer and Data Scientist with over a decade in AI, optimisation, and high-performance computing. He specialises in developing, deploying, and managing advanced ML models, including LLMs and NLP systems, using TensorFlow, PyTorch, and scikit-learn. His expertise extends to GPU-accelerated computing, cloud data platforms (AWS, Azure), and scalable MLOps practices with FastAPI, Flask, and Django. He has led research in energy systems, optimisation, and delivering high-impact solutions for industry and academia. Iman is widely published, with numerous high-impact journal articles and edited books in AI, operations research, and data analytics.
Affiliations and expertise
University of Technology Sydney, Sydney, Australia.

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