Rego C., Alidaee B. (eds.) Metaheuristic Optimization via Memory and Evolution. Tabu Search and Scatter Search

Springer, 2005. — 472 p.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.Part I: Advances for New Model and Solution Approaches
A Scatter Search Tutorial for Graph-Based Permutation Problems
A Multistart Scatter Search Heuristic for Smooth NLP and MINLP Problems
Scatter Search Methods for the Covering Tour Problem
Solution of the Sonet Ring Assignment Problem with Capacity Constraints
Part II: Advances for Solving Classical Problems
A Very Fast Tabu Search Algorithm for Job Shop Problem
Tabu Search Heuristics for the Vehicle Routing Problem
Some New Ideas in TS for Job Shop Scheduling
A Tabu Search Heuristic for the Uncapacitated Facility Location Problem
Adaptive Memory Search Guidance for Satisfiability Problems
Part III: Experimental Evaluations
Lessons from Applying and Experimenting with Scatter Search
Tabu Search for Mixed-Integer Programming
Scatter Search vs. Genetic Algorithms: An Experimental Evaluation with Permutation Problems
Part IV: Review of Recent Developments
Parallel Computation, Co-operation, Tabu Search
Using Group Theory to Construct and Characterize Metaheuristic Search Neighborhoods
Logistics Management: An Opportunity for Metaheuristics
Part V: New Procedural Designs
On the Integration of Metaheuristic Strategies in Constraint Programming
General Purpose Metrics for Solution Variety
Controlled Pool Maintenance for Metaheuristics
Adaptive Memory Projection Methods for Integer Programming
RAMP: A New Metaheuristic Framework for Combinatorial Optimization