Handbook of Metaheuristics. (2018)
- Record Type:
- Book
- Title:
- Handbook of Metaheuristics. (2018)
- Main Title:
- Handbook of Metaheuristics
- Further Information:
- Note: Michel Gendreau, Jean-Yves Potvin, editors.
- Editors:
- Gendreau, Michel, 1955-
Potvin, Jean-Yves, 1956- - Contents:
- Intro; Preface to the Third Edition; Preface to the Second Edition; Preface to the First Edition; Contents; Contributors; 1 Simulated Annealing: From Basics to Applications; 1.1 Introduction; 1.2 Basics; 1.2.1 Local Search (or Monte Carlo) Algorithms; 1.2.2 Metropolis Algorithm; 1.2.3 Simulated Annealing (SA) Algorithm; 1.3 Theory; 1.3.1 Statistical Equilibrium; 1.3.2 Asymptotic Convergence; 1.4 Practical Issues; 1.4.1 Finite-Time Approximation; 1.4.2 Geometric Cooling; 1.4.3 Cooling in Polynomial Time; 1.4.3.1 Initial Temperature c0; 1.4.3.2 Decay of the Control Parameter 1.4.3.3 Length of Markov Chains1.4.3.4 Stopping Criterion; 1.4.3.5 Summary; 1.4.4 Simulation-Based Evaluation; 1.5 Illustrative Applications; 1.5.1 Knapsack Problem; 1.5.1.1 Mathematical Modeling; 1.5.1.2 Simulated Annealing Implementation; 1.5.2 Traveling Salesman Problem; 1.5.2.1 Mathematical Modeling; 1.5.2.2 Simulated Annealing Implementation; 1.6 Large-Scale Aircraft Trajectory Planning; 1.6.1 Mathematical Modeling; 1.6.2 Computational Experiments with SA; 1.7 Conclusion; References; 2 Tabu Search; 2.1 Introduction; 2.2 The Classical Vehicle Routing Problem; 2.3 Basic Concepts 2.3.1 Historical Background2.3.2 Tabu Search; 2.3.3 Search Space and Neighborhood Structure; 2.3.4 Tabus; 2.3.5 Aspiration Criteria; 2.3.6 A Template for Simple Tabu Search; 2.3.7 Termination Criteria; 2.3.8 Probabilistic TS and Candidate Lists; 2.4 Intermediate Concepts; 2.4.1 Intensification; 2.4.2 Diversification; 2.4.3Intro; Preface to the Third Edition; Preface to the Second Edition; Preface to the First Edition; Contents; Contributors; 1 Simulated Annealing: From Basics to Applications; 1.1 Introduction; 1.2 Basics; 1.2.1 Local Search (or Monte Carlo) Algorithms; 1.2.2 Metropolis Algorithm; 1.2.3 Simulated Annealing (SA) Algorithm; 1.3 Theory; 1.3.1 Statistical Equilibrium; 1.3.2 Asymptotic Convergence; 1.4 Practical Issues; 1.4.1 Finite-Time Approximation; 1.4.2 Geometric Cooling; 1.4.3 Cooling in Polynomial Time; 1.4.3.1 Initial Temperature c0; 1.4.3.2 Decay of the Control Parameter 1.4.3.3 Length of Markov Chains1.4.3.4 Stopping Criterion; 1.4.3.5 Summary; 1.4.4 Simulation-Based Evaluation; 1.5 Illustrative Applications; 1.5.1 Knapsack Problem; 1.5.1.1 Mathematical Modeling; 1.5.1.2 Simulated Annealing Implementation; 1.5.2 Traveling Salesman Problem; 1.5.2.1 Mathematical Modeling; 1.5.2.2 Simulated Annealing Implementation; 1.6 Large-Scale Aircraft Trajectory Planning; 1.6.1 Mathematical Modeling; 1.6.2 Computational Experiments with SA; 1.7 Conclusion; References; 2 Tabu Search; 2.1 Introduction; 2.2 The Classical Vehicle Routing Problem; 2.3 Basic Concepts 2.3.1 Historical Background2.3.2 Tabu Search; 2.3.3 Search Space and Neighborhood Structure; 2.3.4 Tabus; 2.3.5 Aspiration Criteria; 2.3.6 A Template for Simple Tabu Search; 2.3.7 Termination Criteria; 2.3.8 Probabilistic TS and Candidate Lists; 2.4 Intermediate Concepts; 2.4.1 Intensification; 2.4.2 Diversification; 2.4.3 Allowing Infeasible Solutions; 2.4.4 Surrogate and Auxiliary Objectives; 2.5 Advanced Concepts; 2.6 Key References; 2.7 Tricks of the Trade; 2.7.1 Getting Started; 2.7.2 More Tips; 2.7.3 Additional Tips for Probabilistic TS 2.7.4 Parameter Calibration and Computational Testing2.8 Conclusion; References; 3 Variable Neighborhood Search; 3.1 Introduction; 3.2 Basic Schemes; 3.3 Some Extensions; 3.4 Changing Formulation Within VNS; 3.4.1 Variable Neighborhood-Based Formulation Space Search; 3.4.2 Variable Formulation Search; 3.5 Primal-Dual VNS; 3.6 VNS for Mixed Integer Linear Programming; 3.6.1 Variable Neighborhood Branching; 3.6.2 VNDS Based Heuristics for MILP; 3.6.2.1 VNDS for 0-1 MILPs with Pseudo-Cuts; 3.6.2.2 A Double Decomposition Scheme; 3.6.2.3 Comparison 3.7 Variable Neighborhood Search for Continuous Global Optimization3.8 Variable Neighborhood Programming (VNP): VNS for Automatic Programming; 3.9 Discovery Science; 3.10 Conclusions; References; 4 Large Neighborhood Search; 4.1 Introduction; 4.1.1 Example Problems; 4.1.2 Neighborhood Search; 4.2 Large Neighborhood Search; 4.3 Adaptive Large Neighborhood Search; 4.3.1 Designing an ALNS Algorithm; 4.3.2 Properties of the ALNS Framework; 4.3.3 Relation to Other Metaheuristics; 4.3.4 Parallelism; 4.4 Applications of LNS and ALNS; 4.4.1 Vehicle Routing Applications; 4.4.2 Other Applications … (more)
- Publisher Details:
- Cham, Switzerland : Springer Nature Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 658.4034
Business
Mathematical optimization -- Handbooks, manuals, etc
Operations research -- Handbooks, manuals, etc
Management science
Operations research
Computer science
BUSINESS & ECONOMICS / Industrial Management
BUSINESS & ECONOMICS / Management
BUSINESS & ECONOMICS / Management Science
BUSINESS & ECONOMICS / Organizational Behavior
Business & Economics -- Operations Research
Computers -- Data Processing
Operational research
Maths for computer scientists
Electronic books
Electronic books - Languages:
- English
- ISBNs:
- 9783319910864
3319910868 - Related ISBNs:
- 9783319910857
- Notes:
- Note: Online resource; title from PDF title page (EBSCO, viewed October 1, 2018).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Physical Locations:
- British Library HMNTS - ELD.DS.331242
- Ingest File:
- 03_015.xml