Towards Energy Efficient Scheduling and Rescheduling for Dynamic Flexible Job Shop Problem
Résumé
Nowadays the migration to green manufacturing is the interest of many companies. Taken into account sustainability in all industrial activities is the main goal of sustainable intelligent manufacturing system. In recent years, the demand for energy and the investment in energy have continued to increase. This work addresses reducing energy consumption when resolving dynamic flexible job-shop scheduling problem under machine breakdowns. A new rescheduling method is proposed to find a reschedule with minimum makespan and with less global energy consumption. The predictive reactive approach is based Particle Swarm Optimization method.