A Hybrid QuantumInspired Evolutionary Programming and Its Application in Tardiness Identical Parallel Machines Scheduling

In this paper, a hybrid quantuminspired evolutionary programming (HQEP) is proposed for identical parallel machines scheduling. The objective is to minimize the total tardiness of all jobs. In HQEP, the concept and principles of quantum computing, such as a quantum bit and superposition of states, are combined with evolutionary programming, and the Q-gate is introduced as a variation operator to drive the individuals toward better solutions. Moreover, an improved representation structure of individuals and mutation operator is proposed for scheduling problems in HQEP. Finally, an illustrative experiment is carried out on different scales of randomly generated test problems. Computational results show that HQEP outperforms evolutionary programming, even with a small population.