A Review of Optimization Methods
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Summary
This introductory chapter reviews a few selected major methods for optimization and mathematical modeling available today and describes them in enough detail so that the reader can understand under what circumstances and why they should be expected to work well in practice.
- Type
- review
- Published
- 2012-01-01
- Cited by
- 2
- References
- 58
- OpenAlex
- https://openalex.org/W7444843
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:59684531
Keywords
Computer science
References
- Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
- A Three-Phase Algorithm for Block-Structured Optimization
- Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
- Using KORBX for military airlift applications
- Optimization by Vector Space Methods
- Dynamic Programming and Optimal Control, Two Volume Set
- Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
- Parallel and distributed computation
- Constrained Optimization and Lagrange Multiplier Methods
- Constrained, non-linear, derivative-free, parallel optimization of continuous, high computing load, noisy objective functions
- Integer and Combinatorial Optimization
- Minimization of functions having Lipschitz continuous first partial derivatives.
- Network Flows: Theory, Algorithms, and Applications
- Conditioning of Quasi-Newton Methods for Function Minimization
- The auction algorithm: A distributed relaxation method for the assignment problem
- An algorithm for integer solutions to linear programs
- Optimization by Simulated Annealing
- A Distributed Evolutionary Simulated Annealing Algorithm for Combinatorial Optimisation Problems
- A family of variable-metric methods derived by variational means
- Linear network optimization - algorithms and codes
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