Energy-saving Oriented Multi-objective Shop Floor Scheduling for Mixed-line Production of Missile Components

Abstract

Aimed at the characteristics of multi-project production, complex process, high energy consumption and tight delivery in the mix-line production of missile structural components, an optimization model for a flexible job-shop scheduling problem considering energy consumption and makespan is developed based on equipment state-energy-consumption curve. A binary hybrid improved genetic algorithm (BH-GA) is proposed to solve the established optimization problem. To improve the searching ability of the algorithm, an information-sharing mechanism based on particle swarm optimization (PSO) is introduced to design the crossover operation of genetic algorithm (GA). In order to avoid falling into local optical solution, a novel temperature update function of simulated annealing algorithm (SA) based on Hill function is used to replace the mutation operation of GA. In addition, a weighted multi-attribute grey target decision model is adopted to select the most satisfactory schedule scheme. The effectiveness of the proposed algorithm is verified by the completely and partially flexible scheduling problems. Finally, the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute in Shanghai, and good effect is gained.