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

Raffaele Carli, Mariagrazia Dotoli, Salvatore Digiesi, Francesco Facchini and Giorgio Mossa
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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

Sustainability, 2020, vol. 12, issue 8, 1-25

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.

Keywords: green warehouse; sustainable scheduling; material handling activity; mobile material handling equipment; warehouse energy management; demand-side management; battery charging; optimization; decision and control (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:8:p:3111-:d:344846

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