Abstract
Aiming at the phenomenon of slow convergence rate and low accuracy of some metaheuristic algorithms , a novel metaheuristic algorithm based on wave function and swarm intelligence is proposed. Swarm intelligence is a collective intelligence of groups of simple agents deals with collective behaviors of decentralized and self-organized swarms, which result from the local interactions of individual components with one another and with their environment. Wave function is introduced to accelerate the convergence speed of proposed algorithm. Standard deviation can ensure the dispersion of the population to prevent premature convergence. The simulation results using Benchmark functions show that the proposed algorithm is effective.
Highlights
Meta heuristics are a class of intelligent self-learning algorithms forfinding near -optimum solutions to hard optimization problems, mimicking intelligent processes and behaviors observed from nature, sociology, thinking, and other disciplines
Aiming at the phenomenon of slow convergence rate and low accuracy of some meta heuristic algorithms, a novel meta heuristic algorithm based on wave function and swarm intelligence is proposed
This paper examined the proposed algorithm and particle swarm optimization when solving benchmark functions
Summary
Meta heuristics are a class of intelligent self-learning algorithms forfinding near -optimum solutions to hard optimization problems, mimicking intelligent processes and behaviors observed from nature, sociology, thinking, and other disciplines. Two major components of any meta heuristic algorithms are: selection of the best solutions and randomization. Genetic algorithms are population-based as they use a set of strings, so is the particle swarm optimization (PSO) which uses multiple agents or particles. Since the evolutionary algorithm can solve some problem that the traditional optimization algorithm cannot do easy, the evolutionary algorithm ,most meta heuristic algorithms are nature-inspired as they have been developed based on some abstraction of nature. Wave Function Algorithm (WFA) is a novel meta heuristic algorithm based on wave function Developing it comes from wave function and swarm intelligence. The conclusion and future work is presented in the last section
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