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.- 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
Table of Contents
1. Multi-objective combinatorial optimization problems: Social, Keywords, and Journal mapsMehdi Toloo, Siamak Talatahari, Iman Rahimi and Amir H. Gandomi2. 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 França3. A survey on links between multiple objective decision making and data envelopment analysisAmineh Ghazi and Farhad Hosseinzadeh LotfiII. New methods for combinatorial optimization problems4. Improved Crow Search Algorithm Based on Arithmetic Cross Over- A Novel Metaheuristic Technique for Solving Engineering Optimization ProblemsS N Kumar, A Lenin Fred, R. Jonisha Miriam, Padmanabhan Parasuraman, Balazs Gulyas, Ajay Kumar Haridhas and Nisha Dayana5. MOGROM: Multi-objective Golden Ratio Optimization AlgorithmBehrooz Vahidi, Amin Foroughi and Abolfazl RahiminejadIII. Application of random-based methods for combinatorial optimization problems6. Multi-Objective Charged System Search for Optimum Location of Bank BranchSiamak Talatahari7. Application of Multi-objective Grey Wolf Optimization in Gasification-based ProblemsSiamak Talatahari8. A VDS-NSGA-II Algorithm for Multi-Year Multi-Objective Dynamic Generation and Transmission Expansion Planning Ali Esmaeel Nezhad9. A Multi-Objective Cuckoo Search Algorithm for Community Detection in Social NetworksFarhad Soleimanian Gharehchopogh and Shafih GhaforiIV. Application of other methods for combinatorial optimization problems10. Finding efficient solutions of the multi-criteria assignment problemEmmanuel Kwasi Mensah, Esmaeil Keshavarz and Mehdi Toloo11. Application of Multi-objective Optimization in Thermal Design and Analysis of Complex Energy Systems Ali Baghernejad and Elnaz Aslanzadeh12. A Multi-Objective Nonlinear Combinatorial Model for Improved Planning of Tour Visits Using a Novel Binary Gaining-Sharing knowledge-based Optimization AlgorithmAli Wagdy wagdy, Said Hassan, Prachi Agrawal and Talari Ganesh13. Variables Clustering Method to Enable Planning of Large Supply ChainsEmilio Bertolotti Sr
