Robotic cells scheduling based on hybrid quantum evolutionary algorithm

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.