Energy-Aware Production Scheduling in Flow Shop and Job Shop Environments Using a Multi-Objective Genetic Algorithm

Pablo Vallejos-Cifuentes, Camilo Ramirez-Gomez, Ana Escudero-Atehortua, Elkin Rodriguez Velasquez

    Research output: Contribution to journalArticle in an indexed scientific journalpeer-review

    9 Scopus citations


    The energy-aware scheduling problem is a multi-objective optimization problem where the main goal is to achieve energy savings without affecting productivity in a manufacturing system. In this work, we present an approach for energy-aware flow shop scheduling problem and energy-aware job shop scheduling problem considering the process speed as the main energy-related decision variable. This approach allows one to set the appropriate process speed for every considered operation in the corresponding machine. When the speed is high, the processing time is short but the energy demand increases, and vice versa. Therefore, two objectives are worked together: a production objective, paired with an energy efficiency objective. A generic elitist multi-objective genetic algorithm was implemented to solve both problems. Results from a simple comparative design of experiments and a nonparametric test show that it is possible to smooth the energy demand profile and obtain reductions that average 19.8% in energy consumption. This helps to reduce peak loads and drops on applied energy sources demand, stabilizing the conversion units operational efficiency across the entire operational time with a minimum effect on the production maximum completion time (makespan).

    Original languageEnglish
    Pages (from-to)82-97
    Number of pages16
    JournalEMJ - Engineering Management Journal
    Issue number2
    StatePublished - 3 Apr 2019

    Bibliographical note

    Publisher Copyright:
    © 2019, © 2019 Taylor & Francis.


    • Economics of engineering
    • Energy Efficiency
    • Flow Shop
    • Job Shop
    • Multi-Objective Optimization
    • Production Scheduling
    • Strategic and operation management
    • Systems engineering

    Types Minciencias

    • Artículos de investigación con calidad A2 / Q2


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