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Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

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  • Tamás Bányai

    (Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary)

Abstract

Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

Suggested Citation

  • Tamás Bányai, 2018. "Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions," Energies, MDPI, vol. 11(7), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1833-:d:157679
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    References listed on IDEAS

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    5. Li, Qiaoru & Wang, Yuanyuan & Li, Kun & Chen, Liang & Wei, Zhenlin, 2019. "Evolutionary dynamics of the last mile travel choice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    6. Techane Bosona, 2020. "Urban Freight Last Mile Logistics—Challenges and Opportunities to Improve Sustainability: A Literature Review," Sustainability, MDPI, vol. 12(21), pages 1-20, October.

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