A novel cultural algorithm for real-parameter optimization

Abstract

The intellects-masses optimizer (IMO) is a new variant of cultural algorithm, which is used to solve continuous numerical optimization problems. The proposed method divides its population into two sub-populations, one that contains the fittest individuals (called the intellects) and the other sub-population, which includes the rest of the individuals in the population (called the masses). The two sub-populations evolve in parallel and influence each other. IMO is a simple, easy to code approach that has few, easy to tune parameters. The performance of IMO is investigated on 25 problems; five of them are real-world engineering problems and six high-dimensional problems. IMO is compared with 6 other state-of-the-art swarm intelligence approaches on the 25 problems. The results show that IMO generally outperforms the other approaches.

Keywords:

• cultural algorithms
• swarm intelligence
• metaheuristics
• particle swarm optimization
• artificial bee colony
• stochastic search

2010 AMS Subject Classifications:

• 65M12
• 65N12
• 76N15
• 86A10
• 75N15

Disclosure Statement

No potential conflict of interest was reported by the author.