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Comparison of Bioinspired Computation and Optimization Techniques


Affiliations
1 Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan
 

In this article we focus on the bioinspired algorithms and their computational classification. The basic ideas and various techniques developed recently are described. The research outcomes in the computational area of solution optimization are presented for different problems, i.e. mathematical, combinatorial, exact approximation and multiple objective optimization. Moreover, evolutionary, stochastic and swarm optimization algorithms are discussed. All these areas have principles of extracting natural concepts in the form of mathematics and algorithms. Nature-inspired algorithms can help explore new dimensions to solve many problems with optimal cost and time. This review shows that bioinspired computing can provide innovative optimal computational algorithms.

Keywords

Bioinspired Computing, Combinatorial Optimization, Computational Complexity, Evolutionary Algorithms.
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  • Comparison of Bioinspired Computation and Optimization Techniques

Abstract Views: 264  |  PDF Views: 70

Authors

Muhammad Kashif Hanif
Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan
Ramzan Talib
Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan
Muhammad Awais
Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan
Muhammad Yahya Saeed
Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan
Umer Sarwar
Department-of-Computer Science, Government-College-University, Faisalabad - 38000, Pakistan

Abstract


In this article we focus on the bioinspired algorithms and their computational classification. The basic ideas and various techniques developed recently are described. The research outcomes in the computational area of solution optimization are presented for different problems, i.e. mathematical, combinatorial, exact approximation and multiple objective optimization. Moreover, evolutionary, stochastic and swarm optimization algorithms are discussed. All these areas have principles of extracting natural concepts in the form of mathematics and algorithms. Nature-inspired algorithms can help explore new dimensions to solve many problems with optimal cost and time. This review shows that bioinspired computing can provide innovative optimal computational algorithms.

Keywords


Bioinspired Computing, Combinatorial Optimization, Computational Complexity, Evolutionary Algorithms.

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DOI: https://doi.org/10.18520/cs%2Fv115%2Fi3%2F450-453