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Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach

Author

Listed:
  • Tamás Bányai

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

  • Béla Illés

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

  • Miklós Gubán

    (Zalaegerszeg Faculty of Business Administration, Budapest Business School, 8900 Zalaegerszeg, Hungary)

  • Ákos Gubán

    (Department of Business Information Technology, Budapest Business School, 1149 Budapest, Hungary)

  • Fabian Schenk

    (Fraunhofer Institute for Factory Operation and Automation, 39106 Magdeburg, Germany)

  • Ágota Bányai

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

Abstract

The just-in-sequence inventory strategy, as an important part of the supply chain solutions in the automotive industry, is based on feedback information from the manufacturer. The performance, reliability, availability and cost efficiency are based on the parameters of the members of the supply chain process. To increase the return on assets (ROA) of the manufacturer, the optimization of the supply process is unavoidable. Within the frame of this paper, the authors describe a flower pollination algorithm-based heuristic optimization model of just-in-sequence supply focusing on sustainability aspects, including fuel consumption and emission. After a systematic literature review, this paper introduces a mathematical model of just-in-sequence supply, including assignment and scheduling problems. The objective of the model is to determine the optimal assignment and schedule for each sequence to minimize the total purchasing cost, which allows improving cost efficiency while sustainability aspects are taken into consideration. Next, a flower pollination algorithm-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase cost-efficiency in just-in-sequence solutions.

Suggested Citation

  • Tamás Bányai & Béla Illés & Miklós Gubán & Ákos Gubán & Fabian Schenk & Ágota Bányai, 2019. "Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach," Sustainability, MDPI, vol. 11(14), pages 1-26, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:14:p:3850-:d:248538
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    References listed on IDEAS

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    1. Wenwen Chen & Yangchongyi Men & Noelia Fuster & Celia Osorio & Angel A. Juan, 2024. "Artificial Intelligence in Logistics Optimization with Sustainable Criteria: A Review," Sustainability, MDPI, vol. 16(21), pages 1-22, October.

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