Journal ArticleDOI
Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics
Zne-Jung Lee,Shun-Feng Su,Chou-Yuan Lee +2 more
- Vol. 33, Iss: 1, pp 113-121
TLDR
The proposed algorithm is to enhance the performance of GAs by introducing a greedy reformation scheme so as to have locally optimal offspring and has the best performance when compared to other existing search algorithms.Abstract:
A general weapon-target assignment (WTA) problem is to find a proper assignment of weapons to targets with the objective of minimizing the expected damage of own-force asset. Genetic algorithms (GAs) are widely used for solving complicated optimization problems, such as WTA problems. In this paper, a novel GA with greedy eugenics is proposed. Eugenics is a process of improving the quality of offspring. The proposed algorithm is to enhance the performance of GAs by introducing a greedy reformation scheme so as to have locally optimal offspring. This algorithm is successfully applied to general WTA problems. From our simulations for those tested problems, the proposed algorithm has the best performance when compared to other existing search algorithms.read more
Citations
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Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment
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Applying hybrid meta-heuristics for capacitated vehicle routing problem
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A new Hybrid Electromagnetism-like Algorithm for capacitated vehicle routing problems
Alkın Yurtkuran,Erdal Emel +1 more
TL;DR: The computational results show that the proposed Hybrid Electromagnetism-like Algorithm gives promising results within acceptable computational times when compared to other novel meta-heuristics.
Journal ArticleDOI
A hybrid search algorithm with heuristics for resource allocation problem
Zne-Jung Lee,Chou-Yuan Lee +1 more
TL;DR: A hybrid search algorithm with heuristics for resource allocation problem encountered in practice is proposed that has both the advantages of genetic algorithm and ant colony optimization that can explore the search space and exploit the best solution.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI
Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.