Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model

Chen, Yuh-Wen; Tzeng, Gwo‐Hshiung

doi:10.1016/s0377-2217(99)00439-7

Cited by 88 publications

(35 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, every dimension is correlated to one another more or less in reality, which is not consistent with the additive hypothesis [15]. Therefore, fuzzy measures were applied in this research to deal with relations and weighted values among QS-9000 directives.…”

Section: Establishment Of Fuzzy Measures and Fuzzy Integrals Modelsmentioning

confidence: 92%

Performance evaluation of introducing QS-9000 to the Taiwanese semiconductor industry

Lin

Chen

Jang

et al. 2005

Int J Adv Manuf Technol

View full text Add to dashboard Cite

According to the survey conducted by AIAG in 1999, significant effects of QS-9000 certification included average cost savings of over 6%, a 38% improvement in defect rate and a 23% increase in market share on OEM. However, few manufacturers in semiconductor related industries in Taiwan have been QS-9000 certified to date. The major reason is there is not a complete and efficient set of implementation procedures for introducing QS-9000 and the certifying process. Consequently, methods of performance evaluation based on multiple goals and principles must be applied to assess the performance of the process of introducing QS-9000 to the Taiwanese semiconductor industry. First, the performance index and the performance matrix presented by Hung, Huang, and Chen are applied to assess the certifying importance and ease of implementation of each directive item (goal). Next, related correlation and weighted values among directives (objectives to be improved) of low importance and high easiness, and also of high importance and low easiness, are established using fuzzy measures. Finally, the directives to be improved (goals to be improved) are transformed to an overall performance value during the implementation process (strategy) by fuzzy integrals to define the critical implementation process (strategy) when QS-9000 is introduced to the semiconductor industry, and also to increase the timeliness of system introduction and certification. Management is expected to find the objectives and strategies to be improved related to the introduction of the QS-9000 system, and to certify this process through the complete assessment model presented here. Subsequently, the performance of introducing QS-9000 and certification may be increased after taking into consideration cost and time factors.

show abstract

Section: Establishment Of Fuzzy Measures and Fuzzy Integrals Modelsmentioning

confidence: 92%

Performance evaluation of introducing QS-9000 to the Taiwanese semiconductor industry

Lin

Chen

Jang

et al. 2005

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…The nonadditive fuzzy integral method has been popularly applied in diverse fields including cost analysis [68,69], location selection [57,70,71], eco-tour plan selection [72,73], performance evaluation [74][75][76][77][78], performance and risk measurement [79], operating model evaluation [80], supplier selection [81,82], risk assessment [83], strategy development [84,85], technology innovation [86], and data selection for hyperspectral image sensing [87]. In summary, due to the advantage of better revealing the real environment in a multicriterion decision-making complex, the nonadditive fuzzy integral approach is employed in this study.…”

Section: Methodsmentioning

confidence: 99%

Decision Making for Third Party Logistics Supplier Selection in Semiconductor Manufacturing Industry: A Nonadditive Fuzzy Integral Approach

Hwang

Shen

2015

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The semiconductor industry has a unique vertically disintegrated structure that consists of various firms specializing in a narrow range of the value chain. To ensure manufacturing and logistics efficiency, the semiconductor manufacturers considerably rely on 3PL suppliers to achieve supply chain excellence. However, 3PL supplier selection is a complex decision-making process involving multiple selection criteria. The goal of this paper is to identify the key 3PL selection criteria by employing the nonadditive fuzzy integral approach. Unlike the traditional multicriterion decision-making (MCDM) methods which often assume independence among criteria and additive importance weights, the nonadditive fuzzy integral is a more effective approach to solve the dependency among criteria, vagueness in information, and essential fuzziness of human judgment. In this paper, we demonstrate an empirical case that employs the nonadditive fuzzy integral to evaluate the importance weight of selection criteria and choose the most appropriate 3PL supplier. The research result can become a valuable reference for manufacturing companies operating in comparable situations. Moreover, the systematic framework presented in this study can be easily extended to the analysis of other decision-making domains.

show abstract

“…A fuzzy-based approach and its many variations have been widely used to capture the subjective perceptions of experts across different industries. For example: qualitative safety modelling during the concept design stage (Sii et al, 2001); order preference in evaluating and prioritising supply chain partners (Shukla et al, 2014); partner selection in a multi-agent setting (Ren et al, 2007;Ordoobadi, 2009); the ranking of customer requirements (Kwong and Bai, 2002); handling uncertainty and subjectivity arising in the risk assessment process (Zeng et al, 2007); and capturing the subjective perception of travel cost (Chen and Tzeng, 2001). A fuzzy-based approach is advantageous compared to other approaches because it does not require large amounts of data such as in fault/event, decision and probability trees and Monte Carlo simulation, and more closely resembles human perception (Hudec and Vujošević, 2012;de Reus, 1994).…”

Section: Introductionmentioning

confidence: 99%

Measuring project sustainability maturity level - a fuzzy-based approach

Siew¹,

Balatbat

Carmichael

2016

IJSD

View full text Add to dashboard Cite

Abstract:Traditionally, project management is focused on outcomes such as quality, time and cost, with little consideration for environmental and social issues. While project management maturity has been discussed at length in the literature, there is currently a paucity of research exploring ways to embed sustainability into project management. Being able to measure levels of sustainability attainment in project management will help project owners identify strengths and weaknesses in their current practices. This paper addresses a gap in the literature by: 1) prescribing a set of criteria for assessing project sustainability maturity levels leading to a project sustainability maturity level (PSML) model, and 2) presenting a fuzzy-based approach to measure maturity levels. An example illustrates the various steps involved in the approach. The fuzzy-based approach is seen as appropriate for reflecting the uncertainty in sustainability maturity assessments. The originality of this paper lies in showing how sustainability can be assessed in a progressive manner through maturity levels.

show abstract

Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model

Cited by 88 publications

References 14 publications

Performance evaluation of introducing QS-9000 to the Taiwanese semiconductor industry

Performance evaluation of introducing QS-9000 to the Taiwanese semiconductor industry

Decision Making for Third Party Logistics Supplier Selection in Semiconductor Manufacturing Industry: A Nonadditive Fuzzy Integral Approach

Measuring project sustainability maturity level - a fuzzy-based approach

Contact Info

Product

Resources

About