Nonlinear fusion method for multistage product design decision-making using plant growth simulation algorithm

Yang, Ye; Yang, Qinxia; An, Weilan; Gong, Zheng

doi:10.1016/j.aei.2022.101712

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…Combined with the notion of a fuzzy set proposed by Zadeh [18], many GDM techniques are employed and applied for PDDM. For instance, Yang et al [13] utilized an interval AHP to determine the weights of decisionmaking indicators and decision-makers. Ayag [19] proposed to calculate the weights of indicators and ranking alternatives based on technique for order preference by similarity to an ideal scheme (TOPSIS) and ANP.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Lai et al [12] combined self-reporting, eye-tracking, and electroencephalogram data for the evaluation of product appearance design, and proposed to transfer the probabilistic linguistic term set with interval uncertainty from self-reporting data to a crisp number to facilitate the comparison of automobile appearance design schemes. Yang et al [13] utilized three-parameter interval grey numbers to unify interval numbers and linguistic terms to depict decision-makers' judgement about product design schemes. Nonetheless, in the context of multiple product design stages, each phase may prioritize distinct aspects and employ heterogeneous evaluation criteria.…”

Section: Introductionmentioning

confidence: 99%

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Research on Multistage Heterogeneous Information Fusion of Product Design Decision-Making Based on Axiomatic Design

Yang,

Zuo,

Zhang

et al. 2024

Systems

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The product design process, fraught with uncertainties and ambiguities in its requirements and constraints, commonly traverses multiple stages, each emphasizing distinct design aspects. This engenders heterogeneity in decision-making criteria, rendering the effective integration of information from various stages of product design decision-making (PDDM) a pivotal task in identifying the optimal design solution. Surprisingly, limited research has attended to the challenge of consolidating such heterogeneous information across multiple PDDM stages. To bridge this gap, our study employs real numbers, interval numbers, and linguistic terms to capture the heterogeneous judgments of decision-makers. We fuse the Maximization Deviation Method with the analytic hierarchy process (AHP) for determining indicators’ weights, while decision-makers’ weights are derived through a dual consideration of uncertainty measure using fuzzy entropy and a distance-minimization model applied to the PDDM matrix for achieving consistency. Leveraging the advantage of axiomatic design, product design alternatives are evaluated based on their PDDM information content of PDDM matrices. Given the multistage nature of product design, stages’ weights are computed by assessing the information content and consistency degree of PDDM matrices at each stage. Ultimately, our approach achieves multistage heterogeneous decision-making fusion in product design through information axiom weighting. A case study involving the decision-making process for a specific numerical control machine design illustrates the efficacy of our method in integrating multistage heterogeneous PDDM data, yielding a comprehensive perspective on the viability of product design schemes. Results show that the ranking sequence of the product design schemes solidifies to x3 > x2 > x1 in stages 2 and 3 of PDDM, diverging from the initial order observed in stage 1 (x2 > x3 > x1), while the fused result from the multistage heterogeneous PDDM analysis aligns with the later stages’ rankings, indicating the credibility and persuasiveness are fortified. This methodology thus offers a robust framework for synthesizing and navigating the uncertainties and complexities inherent in multistage heterogeneous PDDM contexts.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Multistage Heterogeneous Information Fusion of Product Design Decision-Making Based on Axiomatic Design

Yang,

Zuo,

Zhang

et al. 2024

Systems

Self Cite

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“…Wang (2022) predicted ice hazard situations in the Ning-Meng Reaches of the Yellow River based on an improved TPIGN decision-making model. Yang et al (2022b) adopted TPIGN to portray decision-makers' judgments of product design schemes and then constructed a decision-making model for product design. Zheng et al (2022) presented a multi-attribute case retrieval method for heterogeneous data including TPIGN based on bidirectional projection and TODIM model.…”

Section: Introductionmentioning

confidence: 99%

Three-parameter interval grey number dynamic TOPSIS method based on comprehensive similarity

Zhang

Shen

2023

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PurposeThree-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.Design/methodology/approachFirst, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.FindingsTo evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.Originality/valueThe proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.

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Trust-based consensus reaching process for product design decision-making with heterogeneous information

Yang

Lyu

Yang

et al. 2023

Advanced Engineering Informatics

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Nonlinear fusion method for multistage product design decision-making using plant growth simulation algorithm

Cited by 5 publications

References 38 publications

Research on Multistage Heterogeneous Information Fusion of Product Design Decision-Making Based on Axiomatic Design

Research on Multistage Heterogeneous Information Fusion of Product Design Decision-Making Based on Axiomatic Design

Three-parameter interval grey number dynamic TOPSIS method based on comprehensive similarity

Trust-based consensus reaching process for product design decision-making with heterogeneous information

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