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Abstract
For vehicle routing optimization problem in the underground mine, a famous NP- Hard problem is put forward. This paper uses improved ant colony algorithm (ACA) to solve the problem. Basic ant colony algorithm (ACA) has many shortages, such as long searching time， slow convergence rate and easily limited to local optimal solution etc. The improved ant colony algorithm is proposed to overcome these shortcomings and improve its performance adaptively. In every iteration of the ant colony algorithm, adaptive evaporating coefficient is selected to control the convergence rate at first. And the power of this approach was demonstrated on a test case. The results derived from basic ACA and the improved ACA are compared and analyzed in the experiment. It proved that the improved ant colony algorithm is effective
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