Fuzzy relation weighted minimax programming with addition-min composition

Yang, Xin; Qiu, Jianjun; Guo, Hui-Mei; Yang, Xiaopeng

doi:10.1016/j.cie.2020.106644

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…Several resolution method were proposed for the optimization problem with a linear objective function and the addition-min fuzzy relation inequality constraints [10,11,27]. For decreasing the network congestion in the P2P file sharing system, X. Yang et al [12,28,29] further established and investigated the corresponding min-max programming subject to the addition-min fuzzy relation inequalities system. Moreover, the relevant multiple objective optimization problem was also studied, which allowed the system manager to consider three objectives (system congestion, cost, and penalty) simultaneously [30].…”

Section: Introductionmentioning

confidence: 99%

Short Note on “Nonlinear Optimization Problem Subjected to Fuzzy Relational Equations Defined by Dubois-Prade Family of t-Norms”

Liu

Hayat

Yang

2021

Frontiers in Artificial Intelligence and Applications

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This short note aims to make some modification for improving the results presented in [1]. A. Ghodousian et al. discussed the resolution of a system of max-Dubois-Prade fuzzy relation equations based on their proposed index sets Ji, i ∈ I. It is found that not every e ∈ E = J1 × J2 × ⋯ × Jm corresponds to a solution. To overcome this flaw, we modify the expression of the index sets, denoted by J=i , i ∈ I. Based on the modified index sets, resolution of the max-Dubois-Prade fuzzy relation equations becomes easier, regarding the computational cost.

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