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<p>This manuscript presents an analytical fleet-sizing module developed for the Open Platform for Innovation in Logistics (OPIL) within the European Horizon 2020 project “Better Factory“. The module provides a deterministic capacity estimation method for calculating the required number of logistics agents, such as automated guided vehicles, forklifts, or human operators, needed to satisfy predefined material flow demands under steady-state conditions. The approach extends a classical analytical framework by incorporating matrix-based representations of material flows and distances together with agent-specific operational parameters. It is designed to support early-stage logistics planning and system scaling, particularly in small and medium-sized enterprises, where accessible and transparent decision-support tools are essential. The module is implemented as an independent application and its applicability is demonstrated through two industrial case studies involving material transport and inspection tasks. The results illustrate how the proposed analytical framework can support practical decision-making in logistics system design within clearly defined operational assumptions.</p>

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Analytical fleet-sizing method for the Open Platform for Innovation in Logistics (OPIL)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月9日

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  • Ladislav Körösi,
  • František Duchoň

摘要

This manuscript presents an analytical fleet-sizing module developed for the Open Platform for Innovation in Logistics (OPIL) within the European Horizon 2020 project “Better Factory“. The module provides a deterministic capacity estimation method for calculating the required number of logistics agents, such as automated guided vehicles, forklifts, or human operators, needed to satisfy predefined material flow demands under steady-state conditions. The approach extends a classical analytical framework by incorporating matrix-based representations of material flows and distances together with agent-specific operational parameters. It is designed to support early-stage logistics planning and system scaling, particularly in small and medium-sized enterprises, where accessible and transparent decision-support tools are essential. The module is implemented as an independent application and its applicability is demonstrated through two industrial case studies involving material transport and inspection tasks. The results illustrate how the proposed analytical framework can support practical decision-making in logistics system design within clearly defined operational assumptions.