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<p>Most existing research on rental and leased equipment relies on idealized assumptions, such as explicit parameters of Weibull-distributed failure rates and maintenance fully handled by the owner, often overlooking operational uncertainty and limited information sharing between owners and users. To address these limitations, this paper proposes a bi-objective fuzzy probabilistic framework aimed at optimizing profit allocation between two echelons of a rental-based supply chain. The approach incorporates the system stochastic fluctuations and introduces fuzzy parameters to more accurately reflect real-world uncertainties in maintenance and usage conditions. We develop fuzzy interaction models between the owner and user and apply a Genetic Algorithm-based <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40815_2025_2089_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="14" /> </InlineMediaObject> <EquationSource Format="TEX">\(\alpha \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>α</mi> </math></EquationSource> </InlineEquation>-cut technique to compute the lower and upper bounds of the resulting profit intervals. Extensive computational experiments are performed to elucidate the workability of the proposed method and confirm its validity using pattern search algorithm and possibility theory. Additionally, a sensitivity analysis is conducted to evaluate the influence of rental parameters on both echelon-level and overall supply chain performance. This framework offers a robust and practical decision support tool for rental systems under uncertainty.</p>

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Decision-Making in Rental Manufacturing Equipment Under Imprecise Information Sharing: A Bi-objective Fuzzy Probability Combined Approach

  • 期刊论文

  • 发表日期：

    2025年8月11日

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  • M. Haoues,
  • T. Bentrcia,
  • M. Dahane

摘要

Most existing research on rental and leased equipment relies on idealized assumptions, such as explicit parameters of Weibull-distributed failure rates and maintenance fully handled by the owner, often overlooking operational uncertainty and limited information sharing between owners and users. To address these limitations, this paper proposes a bi-objective fuzzy probabilistic framework aimed at optimizing profit allocation between two echelons of a rental-based supply chain. The approach incorporates the system stochastic fluctuations and introduces fuzzy parameters to more accurately reflect real-world uncertainties in maintenance and usage conditions. We develop fuzzy interaction models between the owner and user and apply a Genetic Algorithm-based \(\alpha \) α -cut technique to compute the lower and upper bounds of the resulting profit intervals. Extensive computational experiments are performed to elucidate the workability of the proposed method and confirm its validity using pattern search algorithm and possibility theory. Additionally, a sensitivity analysis is conducted to evaluate the influence of rental parameters on both echelon-level and overall supply chain performance. This framework offers a robust and practical decision support tool for rental systems under uncertainty.