CAJ | 학술논문

根据不同交叉算子的互补特性，提出了改进量子交叉免疫克隆算法（improved quantum crossover immune cloanl algorithm，IQCICA）。交叉算子由具有深度挖掘和广度挖掘特征的两种算子组成，并通过适当的参数控制两种算子的选择。将该算法应用于著名的组合优化问题—旅行商问题（traveling salesman problems，TSP），并将计算结果与其它算法进行了对比分析。仿真结果表明，混合量子交叉免疫克隆选择算法能有效平衡全局和局部搜索能力，有着较好的收敛速度和稳定性。
근거불동교차산자적호보특성，제출료개진양자교차면역극륭산법（improved quantum crossover immune cloanl algorithm，IQCICA）。교차산자유구유심도알굴화엄도알굴특정적량충산자조성，병통과괄당적삼수공제량충산자적선택。장해산법응용우저명적조합우화문제—여행상문제（traveling salesman problems，TSP），병장계산결과여기타산법진행료대비분석。방진결과표명，혼합양자교차면역극륭선택산법능유효평형전국화국부수색능력，유착교호적수렴속도화은정성。
An improved quantum crossover immune clonal algorithm (IQCICA)was proposed based on two crossovers with complementary characteristics.The hybrid crossover consists of two crossovers with exploitation and exploration characteristics respectively.A user-defined parameter was used to select the crossover.The improved algorithm was used to solve the famous combinatorial optimization problems-Traveling Salesman Problems (TSP).Comparison was also performed with other algorithms.Simulation results showed that the improved algorithm had better convergence and stability,and could effectively balance the global and local search capabilities.