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Sustainable Scheduling of Material Handling Activities in Labor-Intensive Warehouses: A Decision and Control Model

Author

Listed:
  • Raffaele Carli

    (Department of Electrical and Information Engineering, Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy)

  • Mariagrazia Dotoli

    (Department of Electrical and Information Engineering, Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy)

  • Salvatore Digiesi

    (Department of Mechanics, Mathematics and Management, Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy)

  • Francesco Facchini

    (Department of Mechanics, Mathematics and Management, Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy)

  • Giorgio Mossa

    (Department of Mechanics, Mathematics and Management, Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy)

Abstract

In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO 2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously.

Suggested Citation

  • Raffaele Carli & Mariagrazia Dotoli & Salvatore Digiesi & Francesco Facchini & Giorgio Mossa, 2020. "Sustainable Scheduling of Material Handling Activities in Labor-Intensive Warehouses: A Decision and Control Model," Sustainability, MDPI, vol. 12(8), pages 1-25, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3111-:d:344846
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    References listed on IDEAS

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    Cited by:

    1. Hyun-woo Jeon & Ahmad Ebrahimi & Ga-hyun Lee, 2023. "A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems," Sustainability, MDPI, vol. 15(20), pages 1-25, October.
    2. Izabela Kudelska & Rafal Niedbal, 2021. "The Impact of Organizational Change on the Improvement of the Picking Process in a Logistics Center – A Case Study," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 882-892.
    3. Tiziana Modica & Sara Perotti & Marco Melacini, 2021. "Green Warehousing: Exploration of Organisational Variables Fostering the Adoption of Energy-Efficient Material Handling Equipment," Sustainability, MDPI, vol. 13(23), pages 1-15, November.
    4. Kateryna Czerniachowska & Radosław Wichniarek & Krzysztof Żywicki, 2023. "A Model for an Order-Picking Problem with a One-Directional Conveyor and Buffer," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    5. Vlado Popović & Milorad Kilibarda & Milan Andrejić & Borut Jereb & Dejan Dragan, 2021. "A New Sustainable Warehouse Management Approach for Workforce and Activities Scheduling," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    6. Giacomo Lanza & Mauro Passacantando & Maria Grazia Scutellà, 2024. "Matheuristic approaches to the green sequencing and routing problem," Flexible Services and Manufacturing Journal, Springer, vol. 36(3), pages 994-1045, September.
    7. Ahmad Ebrahimi & Hyun-woo Jeon & Sang-yeop Jung, 2023. "Improving Energy Consumption and Order Tardiness in Picker-to-Part Warehouses with Electric Forklifts: A Comparison of Four Evolutionary Algorithms," Sustainability, MDPI, vol. 15(13), pages 1-28, July.

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