Quantum Ant Colony Algorithm for the Multi-task Coalition Problem

With concentration on the defects of ant colony algorithm as not-high precision and much iteration existing in the algorithm of multi-task coalition problem(MTCP),this dissertation utilized the characteristics of quantum computation simultaneously processing substantial quanta in parallel to put forward quantum ant colony algorithm on MTCP.First,it utilized quantum superposition states to give quantum code based on Agent,making each Agent occupy 2 positions in the space;Second,in order for the rotation angle to obtain proper size and direction,it posed the self-adaptive and corrective rotation angle adjusting strategy on the basis of pheromone;Finally,it gave ant algorithm-seeking strategy based on the quantum states by monitoring on the quantum code.Substantial simulation experiments show that,compared with existing algorithms,this one can not only obtain better algorithm,but also improve the convergence speed prominently.