Optimization for Multi-Resource Allocation and Leveling Based on a Self-Adaptive Ant Colony Algorithm

In this paper, Optimization of multi-resource allocation and leveling is studied. A mathematical model of multi-resource allocation and leveling problem for bi-objective and multi-restricted condition is set up. A self-adaptive ant colony algorithm for the problem is presented. According to the topological relations of network graph, we develop the method of serial scheduling generation scheme of the tour network of ants, self-adaptive adjusting route choice probability and dynamic adjusting volatile coefficient. Then a multi-resource allocation and leveling problem is shown. The results indicated that the self-adaptive ant colony algorithm can approach a superior solution. Comparison with GAs and ant colony algorithm, this method is superior at computed time and convergence rate. Finally, the self-adaptive ant colony algorithm can effectively solve large scale multi-resource allocation and leveling problem.