Optimization of Job Shop Scheduling Problem with Noise Consideration

All participants in the logistics chain are realizing the significance of minimizing their environmental impacts. Presently, this concept is progressing towards a comprehensive improvement in all links of the supply chain through a principle called the ‘clean supply chain’. In this context, the production process must be more aligned with this direction, shifting from a logic of maximizing productivity towards an alternative that ensures green production, specifically addressing scheduling issues in the production workshops. However, various challenging scheduling problems have been explored in the literature. This paper aims to solve a job shop scheduling problem (JSP) that considers the impact of noise. Optimization of JSP is based on a combination of three objectives: Makespan, energy and noise. The developed model is solved using the particle swarm optimization (PSO) algorithm. The proposed algorithm is tested through a case study. The simulation results indicate the effect of noise consideration in the global affectation of jobs related to JSP. PSO demonstrates his performances in solving JSP considering noise as an objective to attempt.