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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.


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