A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

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Metaheuristics: From Design to Implementation

Economics and Information Theory

Variable neighborhood search: Principles and applications

Strategic facility location: A review

This paper presents a framework for studying the concepts of fit and flexibility in the field of Strategic Human Resource Management (Strategic HRM) focusing on HRM practices, employee skills, and employee behaviors and reviews past conceptual and empirical work within that framework. A model of Strategic HRM is presented and this model is used to explore the concepts of fit and flexibility as they apply to Strategic HRM. The concepts of resource and coordination flexibility are applied to Strategic HRM, and the implications of the framework for both the practice of and research on Strategic HRM are discussed.

Toward a Unifying Framework for Exploring Fit and Flexibility in Strategic Human Resource Management

Dynamic capabilities through continuous improvement infrastructure

Equity measurement in facility location analysis: A review and framework

Multiobjective analysis of facility location decisions

Undoubtedly, humans have been analyzing the effectiveness of locational decisions since they inhabited their first cave. We use the term “facility” here in its broadest sense. That is, it is meant to include entities such as air and maritime ports, factories, warehouses, retail outlets, schools, hospitals, day-care centers, bus stops, subway stations, electronic switching centers, computer concentrators and terminals, rain gages, emergency warning sirens, and satellites, to name but a few that have been analyzed in the research literature. The ubiquity of locational decision-making has led to a strong interest in location analysis and modeling within the operations research and management science community. The long and voluminous history of location research results from several factors. First, location decisions are frequently made at all levels of human organization from individuals and households to firms, government agencies and even international agencies. Second, such decisions are often strategic in nature. That is, they involve large sums of capital resources and their economic effects are long term. In the private sector they have a major influence on the ability of a firm to compete in the market place. In the public sector they influence the efficiency by which jurisdictions provide public services and the ability of these jurisdictions to attract households and other economic activity. Third, they frequently impose economic externalities. Such externalities include pollution, congestion, and economic development, among others. Fourth, location models are often extremely difficult to solve, at least optimally. Even the most basic models are computationally intractable for large problem instances. In fact, the computational complexity of location models is a major reason that the widespread interest in formulating and implementing such models did not occur until the advent of high-speed digital computers. Finally, location models are application specific. That is, their structural form (the objectives, constraints and variables) is determined by the particular location problem under study. Consequently, there does not exist a general location model that is appropriate for all potential or existing applications.

3 Discrete Network Location Models

A number of new location models which utilize the notion of coverage were developed, tested and utilized in a study of the Baltimore City Fire Protection System. These models extend the location decision to include not only specification of the sites of the basic facilities but also the distribution of specialized equipment and/or manpower among those sites. They are seen as more realistic representations of the location decisions which are required in public sector applications.

David A. Schilling

Papers

Dynamic capabilities through continuous improvement infrastructure

Equity measurement in facility location analysis: A review and framework

Multiobjective analysis of facility location decisions

3 Discrete Network Location Models

The Team/Fleet Models for Simultaneous Facility and Equipment Siting