Metaheuristic Search Concepts : A Tutorial with Applications to Production and Logistics

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Metaheuristic Search Concepts; Preface; Contents; Part IPreliminaries; Chapter 1Introduction; Chapter 2The Knapsack Problem and StraightforwardOptimization Methods; 2.1 The Reference Problem; 2.2 An Additional Greedy Approach; 2.3 Solving the Knapsack Problem by Enumeration; 2.4 Branch and Bound; 2.5 Summary; Chapter 3Search Heuristics; 3.1 Search Heuristics Based on Repeated Solution Construction; 3.1.1 Randomized Search by Solution Construction; 3.1.2 Memory-based Search by Solution Construction; 3.2 Search Heuristics Based on Repeated Solution Modification

3.2.1 Allowing Deteriorations only in Dead-ends3.2.2 Allowing Deteriorations at any Time; 3.3 Search Heuristics Based on Repeated SolutionRecombination; Part IIMetaheuristics; Chapter 4Metaheuristics in General; 4.1 Intensification and Diversification; 4.2 Algorithmic View; 4.3 Defining the Term "Metaheuristic"; 4.4 Summary; Chapter 5Metaheuristics Based on Solution Construction; 5.1 Greedy Randomized Adaptive Search Procedure; 5.1.1 Main Components of Greedy Randomized Adaptive SearchProcedures; 5.1.2 Algorithmic View; 5.1.3 Problem Related Aspects; 5.1.4 Intensification / Diversification

5.2 Ant Colony Optimization5.2.1 Application to Optimization Problems; 5.2.2 Main Components of Ant Colony Optimization; 5.2.3 Algorithmic View; 5.2.4 Problem Related Aspects; 5.2.5 Intensification / Diversification; Chapter 6Metaheuristics Based on Solution Modification; 6.1 Local Search as a Common Principle; 6.1.1 The Link Between Solution Modification and Local Search; 6.1.2 Solution Processing Schemes; 6.1.3 Problem Related Aspects; 6.1.4 Creating the Initial Solution; 6.1.5 Simple Improvement-based Local Search; 6.2 Tabu Search; 6.2.1 Main Components of Tabu Search

6.2.2 Algorithmic View6.2.3 The Tabu List; 6.2.4 Problem Related Aspects; 6.2.5 Intensification / Diversification; 6.3 Threshold Accepting; 6.3.1 Main Components of Threshold Accepting; 6.3.2 Algorithmic View; 6.3.3 Problem Related Aspects; 6.3.4 Intensification / Diversification; 6.4 Simulated Annealing; 6.4.1 Homogenous vs. Inhomogenous Simulated Annealing; 6.4.2 Annealing Schedules; 6.4.3 Main Components of Simulated Annealing; 6.4.4 Algorithmic View; 6.4.5 Problem Related Aspects; 6.4.6 Intensification / Diversification; Chapter 7Metaheuristics Based on SolutionRecombination

7.1 Genetic Algorithm7.1.1 Main Components of Genetic Algorithms; 7.1.2 Algorithmic View; 7.1.3 Problem Related Aspects; 7.1.4 Description of the Components of a Genetic Algorithm; 7.1.5 Infeasibility; 7.1.6 Intensification / Diversification; 7.2 Scatter Search; 7.2.1 Main Components of Scatter Search; 7.2.2 Algorithmic View; 7.2.3 Intensification / Diversification; Chapter 8Summarizing Remarks on Metaheuristics; 8.1 Systematization Approaches; 8.1.1 Systematization by Basic Principle; 8.1.2 Alternative Taxonomies; 8.2 Further Metaheuristics; 8.2.1 Variable Neighborhood Search

8.2.2 Guided Local Search

10.1007/978-3-642-11343-7 [DOI]

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