Colony location algorithm for combinatorial optimization

In this paper we propose a novel algorithm called as colony location algorithm (CLA). It mimics the phenomena in biotic community that colonies of species can locate in the places most suitable to their growth. The factors working on the species location such as the nutrient of soil, resource competition between species, growth and decline process, and effect on environment can be considered in CLA via the nutrient function, growth and decline rates, environment evaluation function and fertilization strategy. CLA is applied to solve the classical combinatorial optimization problems, such as assignment problem, traveling salesman problem and quadratic assignment problem. The computation results show us that CLA can achieve the optimal solution with higher possibility and shorter running time.

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