A NSGA-II Approach for Energy-Efficient Flexible Flow Shop Scheduling with Renewable Energy and Storage Integration
Conférence : Communications orales sans actes dans un congrès international ou national
Manufacturing industries face increasing pressure to reduce energy costs while maintai ning production efficiency. Time-of-use electricity pricing structures offer opportunities for cost reduction through strategic production scheduling. Integrating renewable
energy sources such as wind and Photovoltaic, along with Energy Storage System further enhances sustainability and economic benefits. This work presents a multi-objective optimization approach using the Non-dominated Sorting Genetic Algorithm II based on an Order-Oriented Modeling Scheme formulation to address the bi-objective problem of minimizing makespan and total energy cost in a Flexible Flow Shop Scheduling Problem.