Ebook: Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search
- Tags: Operations Research Mathematical Programming, Optimization, Operations Research/Decision Theory, Appl.Mathematics/Computational Methods of Engineering
- Series: Operations Research/Computer Science Interfaces Series 30
- Year: 2005
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
From the preface:
…Where Are We Headed?
The chapters of this book provide a series of landmarks along the way as we investigate and seek to better understand the elements of tabu search and scatter search that account for their successes in an astonishingly varied range of applications. The contributions of the chapters are diverse in scope, and are not uniform in the degree that they plumb or take advantage of fundamental principles underlying TS and SS. Collectively, however, they offer a useful glimpse of issues that deserve to be set in sharper perspective, and that move us farther along the way toward dealing with problems whose size and complexity pose key challenges to the optimization methods of tomorrow...
Fred Glover
University of Colorado
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
From the preface:
…Where Are We Headed?
The chapters of this book provide a series of landmarks along the way as we investigate and seek to better understand the elements of tabu search and scatter search that account for their successes in an astonishingly varied range of applications. The contributions of the chapters are diverse in scope, and are not uniform in the degree that they plumb or take advantage of fundamental principles underlying TS and SS. Collectively, however, they offer a useful glimpse of issues that deserve to be set in sharper perspective, and that move us farther along the way toward dealing with problems whose size and complexity pose key challenges to the optimization methods of tomorrow...
Fred Glover
University of Colorado
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
From the preface:
…Where Are We Headed?
The chapters of this book provide a series of landmarks along the way as we investigate and seek to better understand the elements of tabu search and scatter search that account for their successes in an astonishingly varied range of applications. The contributions of the chapters are diverse in scope, and are not uniform in the degree that they plumb or take advantage of fundamental principles underlying TS and SS. Collectively, however, they offer a useful glimpse of issues that deserve to be set in sharper perspective, and that move us farther along the way toward dealing with problems whose size and complexity pose key challenges to the optimization methods of tomorrow...
Fred Glover
University of Colorado
Content:
Front Matter....Pages i-xiii
A Scatter Search Tutorial for Graph-Based Permutation Problems....Pages 1-24
A Multistart Scatter Search Heuristic for Smooth NLP and MINLP Problems....Pages 25-57
Scatter Search Methods for the Covering Tour Problem....Pages 59-91
Solution of the SONET Ring Assignment Problem with Capacity Constraints....Pages 93-116
A Very Fast Tabu Search Algorithm for Job Shop Problem....Pages 117-144
Tabu Search Heuristics for the Vehicle Routing Problem....Pages 145-163
Some New Ideas in TS for Job Shop Scheduling....Pages 165-190
A Tabu Search Heuristic for the Uncapacitated Facility Location Problem....Pages 191-211
Adaptive Memory Search Guidance for Satisfiability Problems....Pages 213-227
Lessons from Applying and Experimenting with Scatter Search....Pages 229-246
Tabu Search for Mixed Integer Programming....Pages 247-261
Scatter Search vs. Genetic Algorithms....Pages 263-282
Parallel Computation, Co-operation, Tabu Search....Pages 283-302
Using Group Theory to Construct and Characterize Metaheuristic Search Neighborhoods....Pages 303-328
Logistics Management....Pages 329-356
On the Integration of Metaheuristic Strategies in Constraint Programming....Pages 357-371
General Purpose Metrics for Solution Variety....Pages 373-385
Controlled Pool Maintenance for Metaheuristics....Pages 387-424
Adaptive Memory Projection Methods for Integer Programming....Pages 425-440
RAMP: A New Metaheuristic Framework for Combinatorial Optimization....Pages 441-460
Back Matter....Pages 461-466
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
From the preface:
…Where Are We Headed?
The chapters of this book provide a series of landmarks along the way as we investigate and seek to better understand the elements of tabu search and scatter search that account for their successes in an astonishingly varied range of applications. The contributions of the chapters are diverse in scope, and are not uniform in the degree that they plumb or take advantage of fundamental principles underlying TS and SS. Collectively, however, they offer a useful glimpse of issues that deserve to be set in sharper perspective, and that move us farther along the way toward dealing with problems whose size and complexity pose key challenges to the optimization methods of tomorrow...
Fred Glover
University of Colorado
Content:
Front Matter....Pages i-xiii
A Scatter Search Tutorial for Graph-Based Permutation Problems....Pages 1-24
A Multistart Scatter Search Heuristic for Smooth NLP and MINLP Problems....Pages 25-57
Scatter Search Methods for the Covering Tour Problem....Pages 59-91
Solution of the SONET Ring Assignment Problem with Capacity Constraints....Pages 93-116
A Very Fast Tabu Search Algorithm for Job Shop Problem....Pages 117-144
Tabu Search Heuristics for the Vehicle Routing Problem....Pages 145-163
Some New Ideas in TS for Job Shop Scheduling....Pages 165-190
A Tabu Search Heuristic for the Uncapacitated Facility Location Problem....Pages 191-211
Adaptive Memory Search Guidance for Satisfiability Problems....Pages 213-227
Lessons from Applying and Experimenting with Scatter Search....Pages 229-246
Tabu Search for Mixed Integer Programming....Pages 247-261
Scatter Search vs. Genetic Algorithms....Pages 263-282
Parallel Computation, Co-operation, Tabu Search....Pages 283-302
Using Group Theory to Construct and Characterize Metaheuristic Search Neighborhoods....Pages 303-328
Logistics Management....Pages 329-356
On the Integration of Metaheuristic Strategies in Constraint Programming....Pages 357-371
General Purpose Metrics for Solution Variety....Pages 373-385
Controlled Pool Maintenance for Metaheuristics....Pages 387-424
Adaptive Memory Projection Methods for Integer Programming....Pages 425-440
RAMP: A New Metaheuristic Framework for Combinatorial Optimization....Pages 441-460
Back Matter....Pages 461-466
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