Multi-Objective Combinatorial Optimization Problems and Solution Methods

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 INDICE: 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

• ISBN: 978-0-12-823799-1
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 314
• Fecha Publicación: 15/02/2022
• Nº Volúmenes: 1
• Idioma: Inglés