A general model for meta-heuristic algorithms using the concept of fields of forces

A general model is presented to unify the explanation of different meta-heuristic algorithms. This model is based on the concept of fields of forces from physics and covers many meta-heuristic algorithms consisting of Genetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, Big Bang–Big Crunch algorithm and Harmony Search. The properties of these algorithms can be explained using the presented general model that is called the fields of forces (FOF) model. This extension provides efficient means to improve, expand, modify and hybridize the meta-heuristic algorithms. An improved and hybridized algorithm is then developed using the FOF model.

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