Multi-Objective Optimization In Theory and Practice II: Metaheuristic Algorithms

Author(s): Andre A. Keller

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Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic ...
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Preface  promotion: free to download

Pp. i-ii (2)

Andre A. Keller



Acknowledgements  promotion: free to download

Pp. iii

Andre A. Keller



Pareto-Optimal Front Determination

Pp. 1-53 (53)

Andre A. Keller


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Metaheuristic Optimization Algorithms

Pp. 54-83 (30)

Andre A. Keller


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Evolutionary Strategy Algorithms

Pp. 84-113 (30)

Andre A. Keller


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Genetic Search Algorithms

Pp. 114-143 (30)

Andre A. Keller


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Evolution Strategy Algorithms

Pp. 144-156 (13)

Andre A. Keller


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Swarm Intelligence and Co-Evolutionary Algorithms

Pp. 157-172 (16)

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Decomposition-Based and Hybrid Evolutionary Algorithms

Pp. 173-196 (24)

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Many-Objective Optimization and Parallel Computation

Pp. 197-220 (24)

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Design of Test Problems

Pp. 221-234 (14)

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Fifty Collected Test Functions

Pp. 235-267 (33)

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List of Abbreviations  promotion: free to download

Pp. 268-274 (7)

Andre A. Keller



List of Journal Abbreviations in the References  promotion: free to download

Pp. 275-277 (3)

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List of Symbols  promotion: free to download

Pp. 278-280 (3)

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Subject Index  promotion: free to download

Pp. 281-296 (16)

Andre A. Keller