Multi-criteria analysis for dredger dispatching under uncertainty

Yeh, Chung‐Hsing; Deng, Hepu; Pan, Hongqi

doi:10.1057/palgrave.jors.2600656

Cited by 50 publications

(14 citation statements)

References 29 publications

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“…Subjective judgments of experts based on fuzzy techniques have better 1 SERVice QUALity results than concrete application of incorrect information. Since linguistic terms are usually used for expressing the non-exact and subjective opinions of decision-makers, in this research we use them in order to simplify the subjective evaluations of respondents (Herrera & Viedma, 2000;Yeh et al, 1999a;Zadeh, 1975;Zimmerman, 1996).…”

Section: Fuzzy Theorymentioning

confidence: 99%

Evaluation of service quality by using fuzzy MCDM: A case study in Iranian health-care centers

Afkham¹,

Abdi²,

Komijan³

2012

MSL

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Service quality plays an important role in health care systems since hospitals are responsible for people's lives. This study presents an effective approach for evaluating and comparing service qualities of four hospitals. Service quality consists of different attributes and many of them are intangible and difficult to measure. Therefore, we propose a fuzzy method to resolve the ambiguity of the concepts, which are associated with human judgments. SERVQUAL model is used to evaluate the respondents' judgments of service quality and multi attribute decision making approach is implemented for the comparison among hospitals. The paper use analytical hierarchy process (AHP) for obtaining criteria weight and TOPSIS for ranking the cases.

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Section: Fuzzy Theorymentioning

confidence: 99%

Evaluation of service quality by using fuzzy MCDM: A case study in Iranian health-care centers

Afkham¹,

Abdi²,

Komijan³

2012

MSL

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“…In this section we explain how to incorporate the DM's risk attitudes into the general fuzzy MCDM approach. The linguistic approach to modeling risk attitudes in fuzzy MCDM [32][33][34] uses the notion of "optimism" and "pessimism". The key issue for us is to be able to use natural language to describe an appropriate range of attitudes between the extremes of "optimism" and "pessimism".…”

Section: Fuzzy Mcdm By Incorporating Risk Attitudesmentioning

confidence: 99%

Risk and confidence analysis for fuzzy multicriteria decision making

Fenton

Wang

2006

Knowledge-Based Systems

113

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Recent research has recognised that multicriteria decision making (MCDM) should take account of uncertainty, risk and confidence. This paper takes this research forward by using linguistic variables and triangular fuzzy numbers to model the decision maker's (DM) risk and confidence attitudes in order to define a more complete MCDM solution. To illustrate the computation process and demonstrate the feasibility of the results we use a travel problem that has been used previously to assess MCDM techniques. The results show that the method is useful for tackling imprecision and subjectivity in complex, ill-defined and human-oriented decision problems.

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“…In practical situations, a 2 is usually used to represent the most possible value of fuzzy number A, and a 1 and a 3 are used to respectively indicate the lower and upper bounds of fuzzy number A that are often used to illustrate the fuzziness of the data evaluated [9,14]. Linguistic variables have been found intuitively easy to use in expressing the subjectiveness and imprecision of the DM's assessments [6,14]. To facilitate the making of subjective assessments in the evaluation process, linguistic variables approximated by fuzzy numbers and defined as in Table 1 are used.…”

Section: Preliminary Conceptsmentioning

confidence: 99%