Brain storm optimization algorithm

The Brain Storm Optimization (BSO) algorithm is an advanced version of the swarm intelligence algorithms, including Particle Swarm Optimization, it is based on one collective behavior of human being, that is, the traditional brainstorming process. There are two major operations involved in BSO, i.e., convergent operation and divergent operation. A better optimum could be obtained through recursive solution divergence and convergence in the search space. The designed optimization algorithm will naturally have the capability of both convergence and divergence. BSO possesses two kinds of functionalities: capability learning and capacity developing. The divergent operation corresponds to the capability learning while the convergent operation equivalent to capacity developing. The capacity developing focuses on moving the algorithm's search to the areas where higher potential solutions may exist while the capability learning focuses on its actual search towards new solutions from the current solution for single point based optimization algorithms and from the current population of solutions for population-based swarm intelligence algorithms. The capability learning and capacity developing recycle to move individuals towards better if not best solution. The BSO algorithm, therefore, can also be called as a developmental brain storm optimization algorithm. The capacity developing is a top-level learning or macro-level learning methodology. The capacity developing describes the learning ability of an algorithm to adaptively change its parameters, structures, and its learning potential according to the search states of the problem to be solved. In other words, the capacity developing is the search potential possessed by the algorithm. The capability learning is a bottom-level learning or micro-level learning of the algorithm. The capability learning describes the ability for an algorithm to find better solutions from current solutions with the learning capacity it possesses. The BSO algorithm can also be viewed as a combination of swarm intelligence and data mining techniques. Every individual in the brain storm optimization algorithm is not only a solution to the problem to be optimized, but also a data point to reveal the landscapes of the problem. The swarm intelligence and data mining techniques are combined to produce benefits above and beyond what either method could achieve alone.

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