Metaheuristics for Intelligent Electrical Networks

This book describes the fundamental aspects of the new generation of electrical distribution grids, taking as its starting point the opportunities that exist for restructuring existing infrastructure. It emphasizes the incorporation of renewable energy sources into the distribution grid and the need for a technological evolution towards the implementation of smartgrids. The book is organized into two parts: the first part analyzes the integration of distributed energy sources into the distribution grid and the impact of these sources on grid operation. After a general description of the general characteristics of distribution grids and renewable energy sources, it then analyzes the economics of electrical energy distribution networks and presents the impact of these sources on grid operation. The second part of the book then analyzes the various functions which allow for safe operation of the grid and realization of the path towards real world application of smartgrids.

This book describes the main classical combinatorial problems that can be encountered when designing a logistics network or driving a supply chain. It shows how these problems can be tackled by metaheuristics, both separately and using an integrated approach. A huge number of techniques, from the simplest to the most advanced ones, are given for helping the reader to implement efficient solutions that meet its needs. A lot of books have been written about metaheuristics (methods for solving hard optimization problems) and supply chain management (the field in which we find a huge number of combinatorial optimization problems) in the last decades. So, the main reason of this book is to describe how these methods can be implemented for this class of problems.

Introducing the basic concepts in total program control of the intelligent agents and machines, Intelligent Internet Knowledge Networks explores the design and architecture of information systems that include and emphasize the interactive role of modern computer/communication systems and human beings. Here, you’ll discover specific network configurations that sense environments, presented through case studies of IT platforms, electrical governments, medical networks, and educational networks.

This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies – particularly related to robotics – this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented – as well as the results obtained – are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.

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. Contents 1. An Estimation of Distribution Algorithm for Solving Flow Shop Scheduling Problems with Sequence-dependent Family Setup Times, Mansour Eddaly, Bassem Jarboui, Radhouan Bouabda, Patrick Siarry and Abdelwaheb Reba?. 2. Genetic Algorithms for Solving Flexible Job Shop Scheduling Problems, Imed Kacem. 3. A Hybrid GRASP-Differential Evolution Algorithm for Solving Flow Shop Scheduling Problems with No-Wait Constraints, Hanen Akrout, Bassem Jarboui, Patrick Siarry and Abdelwaheb Reba?. 4. A Comparison of Local Search Metaheuristics for a Hierarchical Flow Shop Optimization Problem with Time Lags, Emna Dhouib, Jacques Teghem, Daniel Tuyttens and Ta?cir Loukil. 5. Neutrality in Flow Shop Scheduling Problems: Landscape Structure and Local Search, Marie-El?onore Marmion. 6. Evolutionary Metaheuristic Based on Genetic Algorithm: Application to Hybrid Flow Shop Problem with Availability Constraints, Nadia Chaaben, Racem Mellouli and Faouzi Masmoudi. 7. Models and Methods in Graph Coloration for Various Production Problems, Nicolas Zufferey. 8. Mathematical Programming and Heuristics for Scheduling Problems with Early and Tardy Penalties, Mustapha Ratli, Rachid Benmansour, Rita Macedo, Sa?d Hanafi, Christophe Wilbaut. 9. Metaheuristics for Biobjective Flow Shop Scheduling, Matthieu Basseur and Arnaud Liefooghe. 10. Pareto Solution Strategies for the Industrial Car Sequencing Problem, Caroline Gagn?, Arnaud Zinflou and Marc Gravel. 11. Multi-Objective Metaheuristics for the Joint Scheduling of Production and Maintenance, Ali Berrichi and Farouk Yalaoui. 12. Optimization via a Genetic Algorithm Parametrizing the AHP Method for Multicriteria Workshop Scheduling, Fouzia Ounnar, Patrick Pujo and Afef Denguir. 13. A Multicriteria Genetic Algorithm for the Resource-constrained Task Scheduling Problem, Olfa Dridi, Saoussen Krichen and Adel Guitouni. 14. Metaheuristics for the Solution of Vehicle Routing Problems in a Dynamic Context, Tient? Hsu, Gilles Gon?alves and R?my Dupas. 15. Combination of a Metaheuristic and a Simulation Model for the Scheduling of Resource-constrained Transport Activities, Virginie Andr?, Nathalie Grangeon and Sylvie Norre. 16. Vehicle Routing Problems with Scheduling Constraints, Rahma Lahyani, Fr?d?ric Semet and Beno?t Trouillet. 17. Metaheuristics for Job Shop Scheduling with Transportation, Qiao Zhang, Herv? Manier, Marie-Ange Manier. About the Authors Bassem Jarboui is Professor at the University of Sfax, Tunisia. Patrick Siarry is Professor at the Laboratoire Images, Signaux et Syst?mes Intelligents (LISSI), University of Paris-Est Cr?teil, France. Jacques Teghem is Professor at the Universit

Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.

Metaheuristic Algorithms in Maritime Operations Optimization focuses on the seaside and port side problems regarding the maritime transportation. The book reviews and introduces the most important problems regarding the shipping network design, long-term and short-term scheduling and planning problems in both bulk and container shipping as well as liquid maritime transportation. Application of meta heuristic algorithm is important for these problems, as most of them are hard and time-consuming to be solved optimally.

Air Traffic Management involves many different services such as Airspace Management, Air Traffic Flow Management and Air Traffic Control. Many optimization problems arise from these topics and they generally involve different kinds of variables, constraints, uncertainties. Metaheuristics are often good candidates to solve these problems. The book models various complex Air Traffic Management problems such as airport taxiing, departure slot allocation, en route conflict resolution, airspace and route design. The authors detail the operational context and state of art for each problem. They introduce different approaches using metaheuristics to solve these problems and when possible, compare their performances to existing approaches

Food has a fundamental position in society, ensuring health, happiness and political stability. Consequently, the management of food chains and networks is one of the most important aspects of the modern food industry. Yet food is difficult to handle along long supply chains, with a limited window for storage and handling time, and the risk of spoiling if incorrectly handled or processed. These issues can lead to logistical problems that can severely affect product quality and freshness. Intelligent Agrifood Chains and Networks offers a timely discussion of the current state of food logistics, and indicates the major ICT problems that can occur during production, warehousing, transportation and retailing. Emphasis is given to new technologies and intelligent systems that are able to process time-dependent information, handle emergencies, and support logistics operations in food management. In particular, the authors show how telematics and RFID can be implemented in the supply chain. The book also includes real-life case studies, in which actual food logistics problems and their solutions are presented, demonstrating how systemic and logistics approaches may be combined. The book is directed at academics, researchers, and students seeking the necessary background in terms of the interplay between the food supply chain and ICT. Its comprehensive review of current issues in the food supply chain will be of interest to managers and technicians working in the food industry, while its technological focus will be invaluable to food scientists and technologists working in research and industry environments.