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In the field of swarm intelligence inspired algorithms, particle swarm optimization (PSO) is a renowned meta-heuristic due to its simplicity, performance, and implementation. However, the PSO also have some downsides like stagnation and slow convergence due to improper balance between the diversification and convergence abilities of the population. Therefore, in this paper, solution search process...
Animal Migration Optimization algorithm is stimulated by intelligent conduct of animal while migrating from one place to other place in search of food and secure habitat. This algorithm simulate the behavior of animal that how they shift from existing location to fresh location and how a number of animal depart from the group and other connect with the group. There are mainly two phases namely migration...
Artificial Bee Colony Algorithm (ABC) is very popular algorithm inspired by intelligent food foraging behavior of honey bee in class of nature inspired algorithms. This paper put forward a new algorithm named as Weight driven Position Update Artificial Bee Colony (WdABC) algorithm which update position of employed bee according to variation in weight factor so as to improve the balance between exploration...
Researchers can solve Simple optimization problems using various methods. But differential Evolution (DE) is a method(population based) to solve complex optimization problems in some easy steps that is not possible to handle by mathematical optimization methods. For global optimization problems DE is a probabilistic approach. DE when tested over some bench mark functions and real world problems it...
Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA). ABC is motivated by clever food foraging behavior of honey bees. Comparable to other population based stochastic algorithm ABC also lack balance in exploration of local search reason and exploitation of finest possible solutions in search space. The proposed algorithm is a hybrid of two memetic algorithms; it combines Levy...
Differential Evolution (DE) is a simple and fast population based Nature Inspired Algorithm (NIA). When it is experimented for benchmark problems as well as real world problems it outperformed other population based NIAs and other search metaheuristics in terms of rate of convergence. But it is not an exception in class of population based algorithms, it also show premature convergence and stagnates...
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