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Natural Intelligence for Scheduling, Planning and Packing Problems
Scheduling, planning and packing are ubiquitous problems that can be found in a wide range of real-world settings. These problems transpire in a large variety of forms, and have enormous socio-economic impact. For many years, significant work has been devoted to automating the processes of scheduling, planning and packing using different kinds of methods. However, poor scaling and the lack of flexibility of many of the conventional methods coupled with the fact that most of the real-world problems across the application areas of scheduling, planning and packing nowadays tend to be of large scale, dynamic and full of complex dependencies have made it necessary to tackle them in unconventional...
Black Box Optimization, Machine Learning, and No-Free Lunch Theorems
This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems. Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.
Advances in Computational Logistics and Supply Chain Analytics
This book provides advances in computational logistics and supply chain analytics. The authors include innovative data-driven and learning-based approaches, methods, algorithms, techniques, and tools that have been designed or applied to create and implement a successful logistics and supply chain management process. This book highlights the state of the art and challenges related to the design and the application of computational methods to solve logistic and supply chain management problems. The authors present recent computational logistic methods and supply chain analytics techniques designed and applied to support managers in improving such complex processes. This book broadly covers recent computational methods and techniques applied to ensure continuous improvement of transport, logistic, and supply chain management processes. Readers can rapidly explore these new methods and their applications to solve such complex problems.
Operations Management Research and Cellular Manufacturing Systems: Innovative Methods and Approaches
"This book presents advancements in the field of operations management, focusing specifically on topics related to layout design for manufacturing environments"--Provided by publisher.
Variable Neighborhood Search
This book constitutes the refereed post-conference proceedings of the 6th International Conference on Variable Neighborhood Search, ICVNS 2018, held in Sithonia, Greece, in October 2018. ICVNS 2018 received 49 submissions of which 23 full papers were carefully reviewed and selected. VNS is a metaheuristic based on systematic changes in the neighborhood structure within a search for solving optimization problems and related tasks. The main goal of ICVNS 2018 was to provide a stimulating environment in which researchers coming from various scientific fields could share and discuss their knowledge, expertise, and ideas related to the VNS metaheuristic and its applications.
Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020)
This book highlights the recent research on soft computing and pattern recognition and their various practical applications. It presents 62 selected papers from the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) and 35 papers from the 16th International Conference on Information Assurance and Security (IAS 2020), which was held online, from December 15 to 18, 2020. A premier conference in the field of artificial intelligence, SoCPaR-IAS 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Variable Neighborhood Search
This volume constitutes the proceedings of the 9th International Conference on Variable Neighborhood Search, ICVNS 2023, held in Abu Dhabi, United Arab Emirates, in October 2022. The 11 full papers presented in this volume were carefully reviewed and selected from 29 submissions. The papers describe recent advances in methods and applications of variable neighborhood search.
Variable Neighborhood Search
This volume constitutes the proceedings of the 8th International Conference on Variable Neighborhood Search, ICVNS 2021, held in Abu Dhabi, United Arab Emirates, in March 2021. The 14 full papers presented in this volume were carefully reviewed and selected from 27 submissions. The papers describe recent advances in methods and applications of variable neighborhood search. Chapter “Reduced Variable Neighbourhood Search for the Generation of Controlled Circular Data” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Intelligence and Data Mining in Healthcare
This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Metaheuristics for Production Scheduling
This book describes the potentialities of metaheuristics for solving production scheduling problems and the relationship between these two fields. For the past several years, there has been an increasing interest in using metaheuristic methods to solve scheduling problems. The main reasons for this are that such problems are generally hard to solve to optimality, as well as the fact that metaheuristics provide very good solutions in a reasonable time. The first part of the book presents eight applications of metaheuristics for solving various mono-objective scheduling problems. The second part is itself split into two, the first section being devoted to five multi-objective problems to which metaheuristics are adapted, while the second tackles various transportation problems related to the organization of production systems. Many real-world applications are presented by the authors, making this an invaluable resource for researchers and students in engineering, economics, mathematics and computer science.
