Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure

Abstract

In order to solve the scheduling problem of aircraft moving assembly line in uncertainty environment, this paper proposes a perceptron-dependent fruit fly optimization algorithm(PDFOA) to generate the assembly scheduling template with strong robustness. The proposed PDFOA, taking the fruit fly optimization algorithm as the basis, designs narrow-field osphresis-search operation and narrow-field vision-search operation which is helpful for searching and choosing neighborhood solutions. Simultaneously, the PDFOA sets up a memory library to enhance the global search ability. Finally, simulation experiments are conducted using different testing samples on different job scales. The proposed PDFOA is compared with tabu search, the genetic algorithm and the immune particle swarm optimization algorithm. The results demonstrate the effectiveness of the PDFOA.

Keywords

• failure and repair of equipments
• fruit fly optimization algorithm
• proactive scheduling
• sampling simulation
• robust baseline scheduling