08-16-2017, 09:00 PM
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http://tandfonlinedoi/full/10.1080/08839514.2014.904599
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matlab code cuckoo search algorithm
Cuckoo search (CS) is an optimization algorithm developed by Xin-she Yang and Suash Deb in 2009. It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species).
Some host birds can engage direct conflict with the intruding cuckoos. For example, if a host bird discovers the eggs are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Some cuckoo species such as the New World brood-parasitic Tapera have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in colors and pattern of the eggs of a few chosen host species.
Cuckoo search idealized such breeding behavior, and thus can be applied for various optimization problems. It seems that it can outperform other metaheuristic algorithms in applications.
Cuckoo search (CS) uses the following representations:
Each egg in a nest represents a solution, and a cuckoo egg represents a new solution. The aim is to use the new and potentially better solutions (cuckoos) to replace a not-so-good solution in the nests. In the simplest form, each nest has one egg. The algorithm can be extended to more complicated cases in which each nest has multiple eggs representing a set of solutions.
CS is based on three idealized rules:
Each cuckoo lays one egg at a time, and dumps its egg in a randomly chosen nest;
The best nests with high quality of eggs will carry over to the next generation;
The number of available hosts nests is fixed, and the egg laid by a cuckoo is discovered by the host bird with a probability p_a \in (0,1). Discovering operate on some set of worst nests, and discovered solutions dumped from farther calculations.