The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

MICHEL GENDREAU AND PATRICE MARCOTTE As an academic, Michael Florian has always stood at the forefront of transportation research. This is reflected in the miscellaneous contributions that make the chapters of this book, which are related in some way or another to Michael's interests in both the theoretical and practical aspects of his field. These interests span the areas of Traffic Assignment, Network Equilibrium, Shortest Paths, Railroad problems, De mand models, Variational Inequalities, Intelligent Transportation Systems, etc. The contributions are briefly outlined below. BASSANINI, LA BELLA AND NASTASI determine a track pricing policy for railroad companies through the solution of a generalized Nash game. BEN-AKIVA, BIER LAIRE, KOUTSOPOULOS AND MISHALANI discuss simulation-based estimators of the interactions between supply and demand within a real-time transportation system. BOYCE, BALASUBRAMANIAM AND TIAN analyze the impact of marginal cost pricing on urban traffic in the Chicago region. BROTCORNE, DE WOLF, GENDREAU AND LABBE present a discrete model of dynamic traffic assignment where flow departure is endogenous and the First-In-First-Out condition is strictly enforced. CASCETTA AND IMP ROTA give a rigorous treatment of the problem of estimating travel demand from observed data, both in the static and dynamic cases. CRAINIC, DUFOUR, FLo RIAN AND LARIN show how to obtain path information that is consistent with the link information provided by a nonlinear multimodal model. ERLANDER derives the logit model from an efficiency principle rather than from the classical random utility approach."

Multidisciplinary Scheduling: Theory and Applications is a volume of nineteen reviewed papers that were selected from the sixty-seven papers presented during the First Multidisciplinary International Conference of Scheduling (MISTA). This is the initial volume of MISTA the primary forum on interdisciplinary research on scheduling research. Each paper in the volume has been rigorously reviewed and carefully copyedited to ensure its readability.

The MISTA volume focuses on the following leading edge topics: Fundamentals of Scheduling, Multi-Criteria Scheduling, Personnel Scheduling, Scheduling in Space, Scheduling the Internet, Machine Scheduling, Bin Packing, Educational Timetabling, Sports Scheduling, and Transport Scheduling.

The aim of Metaheuristics: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field. Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.

This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

This book's aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

MICHEL GENDREAU AND PATRICE MARCOTTE As an academic, Michael Florian has always stood at the forefront of transportation research. This is reflected in the miscellaneous contributions that make the chapters of this book, which are related in some way or another to Michael's interests in both the theoretical and practical aspects of his field. These interests span the areas of Traffic Assignment, Network Equilibrium, Shortest Paths, Railroad problems, De mand models, Variational Inequalities, Intelligent Transportation Systems, etc. The contributions are briefly outlined below. BASSANINI, LA BELLA AND NASTASI determine a track pricing policy for railroad companies through the solution of a generalized Nash game. BEN-AKIVA, BIER LAIRE, KOUTSOPOULOS AND MISHALANI discuss simulation-based estimators of the interactions between supply and demand within a real-time transportation system. BOYCE, BALASUBRAMANIAM AND TIAN analyze the impact of marginal cost pricing on urban traffic in the Chicago region. BROTCORNE, DE WOLF, GENDREAU AND LABBE present a discrete model of dynamic traffic assignment where flow departure is endogenous and the First-In-First-Out condition is strictly enforced. CASCETTA AND IMP ROTA give a rigorous treatment of the problem of estimating travel demand from observed data, both in the static and dynamic cases. CRAINIC, DUFOUR, FLo RIAN AND LARIN show how to obtain path information that is consistent with the link information provided by a nonlinear multimodal model. ERLANDER derives the logit model from an efficiency principle rather than from the classical random utility approach."

Multidisciplinary Scheduling: Theory and Applications is a volume of nineteen reviewed papers that were selected from the sixty-seven papers presented during the First Multidisciplinary International Conference of Scheduling (MISTA). This is the initial volume of MISTA the primary forum on interdisciplinary research on scheduling research. Each paper in the volume has been rigorously reviewed and carefully copyedited to ensure its readability.

The MISTA volume focuses on the following leading edge topics: Fundamentals of Scheduling, Multi-Criteria Scheduling, Personnel Scheduling, Scheduling in Space, Scheduling the Internet, Machine Scheduling, Bin Packing, Educational Timetabling, Sports Scheduling, and Transport Scheduling.

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.