Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions

Hocine, Amin; Zhuang, Zheng-Yun; Kouaissah, Noureddine; Li, Der-Chiang

doi:10.1016/j.ejor.2020.02.009

Cited by 41 publications

(15 citation statements)

References 51 publications

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“…Accordingly, to deal with the number of n triangular MFs, 2 log 2n     binary variables, 8n auxiliary constraints, plus 2n sign constraints are required. This handling is better than the model of Hocine et al [17], where 2n binary variables are needed in their model to deal with the number of n triangular MFs. In order to reduce the auxiliary constraints in P1, Proposition 2 is introduced, as follows: ( )…”

Section: Proposed Model For Triangular Mf Formulationmentioning

confidence: 93%

“…Multi-choice goal programming (MCGP, 2007) [1] WA-FMCGP (2020) [17] For quantitative issue For qualitative issue…”

Section: Explore New Areamentioning

confidence: 99%

“…Moreover, MCGP has been widely applied to solve many real-world decision-making problems such as supplier selection [4], [5], house selection [6], sugar and ethanol milling problem [7], selection of locations for coffee shops and renewable-energy facilities [8], [9], supply chain management problem [10], consumer choice problem [11], and catering supplier selection problem [12]. On the other hand, many advanced MCGP relevant methods were subsequently proposed including fuzzy MCGP (FMCGP) [13], multi-segment MCGP [14], multi-coefficient GP [15], MCGP with the conic scalarizing function [16], and weightedadditive fuzzy MCGP (WA-FMCGP) [17].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, Hocine et al [17] proposed a WA-FMCGP method to formulate triangular and trapezoidal MFs. However, there is a major restriction on their method: 2n binary variables were required in their model to formulate n triangular MFs, which becomes time-consuming when the problem size increases.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fuzzy Multi-Choice Goal Programming and Artificial Bee Colony Algorithm for Triangular and Trapezoidal Membership Functions

Chang

Lin

2021

IEEE Access

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Multi-choice goal programming (MCGP) has been widely used to find satisfying solutions for multiple criteria/objective decision problems in which the target value of "the more, the better," or "the less, the better" can easily be obtained. This paper proposes two new models for representing the triangular and trapezoidal membership functions, which improve the efficacy of fuzzy MCGP (FMCGP). Two real-world applications are provided in this study to demonstrate the usefulness of the proposed models. Furthermore, the same problems are resolved by using the proposed nature-inspired optimization method (NIOM) to find the differences between them. While the artificial bee colony (ABC) algorithm is a well-known NIOM technique, studies have shown that it has an excellent performance with high-quality solutions. Thus, this study initially uses the ABC algorithm to find the differences between MCGP and ABC. Finally, some insightful information is obtained from the comparison to contribute to the NIOM and MCGP fields and their respective applications.

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Section: Proposed Model For Triangular Mf Formulationmentioning

confidence: 93%

“…Multi-choice goal programming (MCGP, 2007) [1] WA-FMCGP (2020) [17] For quantitative issue For qualitative issue…”

Section: Explore New Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy Multi-Choice Goal Programming and Artificial Bee Colony Algorithm for Triangular and Trapezoidal Membership Functions

Chang

Lin

2021

IEEE Access

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“…Boostani et al (2018) selected the optimal site for the construction of temporary shelters and the identified criteria are political stability, environmental aspects, social aspects, economic factors, access to energy resources, access to connection networks, centers and other service centers, proximity to relief distribution, proximity to affected areas, telecommunication facilities, land suitability, and infrastructure facilities. Hocine et al (2020) proposed a weighted-additive fuzzy multi-choice goal programming model to select a suitable renewable energy site and the considered criteria include social acceptability, topography and infrastructure energy generation, and unit cost energy.…”

Section: Classification Of Multiple Criteria Decision Making Problems In Civil Engineeringmentioning

confidence: 99%

Applications of Fuzzy Multiple Criteria Decision Making Methods in Civil Engineering: A State-of-the-Art Survey

Wen

Liao

Zavadskas

et al. 2021

Journal of Civil Engineering and Management

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A variety of fuzzy multiple criteria decision making (MCDM) models have been proposed to solve complicated decision-making problems. Many applications have been achieved, especially in the field of civil engineering. To analyze the developments about the fuzzy MCDM methods and their applications in civil engineering in recent years and further explore the future research directions, this study conducts a state of the art survey in which 52 journal papers focusing on the applications of fuzzy MCDM models in civil engineering from 2016 to 2020 are reviewed. We respectively classify these articles according to research problems and research methods. Through the literature review, we get findings in terms of the most concerned decision-making problem, the most widely-used evaluation criterion and the most popular fuzzy MCDM model. Furthermore, we present four aspects of research challenges and corresponding future research directions in the field of civil engineering, which may be helpful for researchers and practitioners to further investigate.

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Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

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The best‐worst method (BWM) is a multi‐criteria decision‐making (MCDM) approach for solving several types of real‐life decision‐making problems. The basic BWM determines the priority order by pairwise comparisons of the best and worst criteria. The strength of the preference assigned via numerical value for linguistic interpretations of relative comparisons ranges from 1 to 9, representing preferences among the criterion. However, the amount of strength is entirely dependent on the choice of the decision‐makers. Though expert's opinions may differ due to various reasons such as incomplete information, lack of knowledge, ambiguity in linguistic terms, and so forth. Therefore, it is highly likely that the expert may provide multiple viewpoints for the preferences values. Thus, this study proposes a novel extension of the BWM named the multi‐choice best‐worst method (MCBWM), dealing with the concept of multiple choices of preference relations to compare the criterion. The MCBWM overcomes the limitation of BWM, where the pairwise preferences in the comparisons are multi‐choice parameters rather than single parametric values. Multiple real‐world MCDM applications are illustrated in experimental studies to show the quality, performance, and applicability of our proposed MCBWM. A detailed comparative analysis of the proposed approach has been done with the well‐known existing decision‐making techniques and their optimal results are compared. The proposed method offers a new direction for the MCDM approaches for solving real‐life problems.

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Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions

Cited by 41 publications

References 51 publications

Fuzzy Multi-Choice Goal Programming and Artificial Bee Colony Algorithm for Triangular and Trapezoidal Membership Functions

Fuzzy Multi-Choice Goal Programming and Artificial Bee Colony Algorithm for Triangular and Trapezoidal Membership Functions

Applications of Fuzzy Multiple Criteria Decision Making Methods in Civil Engineering: A State-of-the-Art Survey

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

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