This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

Swarm intelligence describes the ability of groups of social animals and insects to exhibit highly organized and complex problem-solving behaviors that allow the group as a whole to accomplish tasks which are beyond the capabilities of any one of the constituent individuals. This natural phenomenon is the inspiration for swarm intelligence systems, a class of algorithms that utilizes the emerge...

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavio...

Big data is the slightly abstract phase which describes the relationship between the data size and data processing speed in the system. The many new information technologies the big data deliver dramatic cost reduction, substantial improvements in the required time to perform the computing task or new product and service offerings. The several complicated specific and engineering problems can b...

The research field of swarm intelligence contains various algorithms inspired from the particular survival skills of the creatures in Mother Nature. Many researchers utilize these methods to solve problems in engineering and financial fields. In this review, the concept of four swarm intelligence methods, including Bat Algorithm (BA), Evolved Bat Algorithm (EBA), Cat Swarm Optimization (CSO), a...

Swarm Intelligence is an artificial intelligence discipline which is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviours of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behaviour of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with comp...

In this work, a novel approach of merging two swarm intelligence algorithms is considered – one mimicking the behaviour of ants foraging (Stochastic Diffusion Search [5]) and the other algorithm simulating the behaviour of birds flocking (Particle Swarm Optimisation [17]). This hybrid algorithm is assisted by a mechanism inspired from the behaviour of skeletal muscles activated by motor neurons...

For a decade swarm Intelligence is concerned with the design of intelligent systems by taking inspiration from the collective behaviors of social insects. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and P...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...