中文摘要：

为解决传统智能优化算法在求解自动化制造单元调度问题时易出现早熟、陷入局部最优等问题,提出了混合量子进化算法.该算法采用序列染色体和量子染色体相结合的混合编解码策略,利用构造启发式算法生成初始种群,避免了不可行解的大量产生;为提高算法的优化性能,进化过程中采用序列染色体和量子染色体同步交叉变异策略,并引入了基于图论的不可行解修复策略.通过与遗传算法、基本量子进化算法的对比实验,验证了算法的有效性.

英文摘要：

To overcome premature convergence and local optima of traditional intelligent algorithms on solving the robotic cell scheduling problem,an Hybrid Quantum Evolutionary Algorithm （HQEA） was proposed.In this algorithm,a mixed coding scheme combining the sequence chromosome with the quantum chromosome was developed,and a new constructive heuristic algorithm was designed to generate initial populations to avoid the generation of a great quantity of infeasible solutions.To increase the optimization property of the algorithm,the synchronized crossover and mutation operation strategy was applied.In addition,repaired strategies of infeasible solutions based on the graph theory were also proposed.Through contrast test between Genetic Algorithm （GA） and basic Quantum Evolutionary Algorithm （QEA）,the effectiveness of HQEA was validated.