Evaluation of Design Alternatives' Environmental Performance Using AHP and ER Approaches

Ng, C. Y.; Chuah, Kong Bieng

doi:10.1109/jsyst.2013.2258217

Cited by 35 publications

(13 citation statements)

References 17 publications

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“…AHP was chosen because it was able to accommodate analytical object, both quantitative and qualitative information into mathematical models [20]. Decomposition as the onset would be considered to separate that information by problem into hierarchy based on the results of field survey and literature studies [21].…”

Section: Analytical Hierarchy Process (Ahp)mentioning

confidence: 99%

Vulnerability assessment of residential buildings to tidal flood hazards in Sriwulan Village, Sayung District, Demak Regency

Afifah

Hizbaron

2020

E3S Web Conf.

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Tidal floods are among the destructive hazards to coastal settlements. In December of 2017, extreme tidal floods impacted 3, 500 houses in Sriwulan Village, Sayung District, Demak Regency. This research was intended to (1) asses the vulnerability levels of the residential buildings and (2) analyze the most influencing factors. The assessment was based on the scenarios built with a 150cm-high tidal flood, as observed during the 2017 event and projected for the subsequent five years (2022). The Analytical Hierarchy Process (AHP) and Spatial Multi-Criteria Evaluation (SMCE) were used in four scenarios, namely, hazard, physical, environmental, and economic. The equal scenario was also developed as a comparison to the first four scenarios to achieve the second objective. Based on the physical, environmental, and equal scenarios, 22 houses distributed throughout most of the areas of Nyangkringan Sub-Village fell into the category of highly vulnerable. The most determinants of the vulnerability are related to the physical and environmental parameters. The former includes the design flood elevation, building maintenance, and building materials, while the latter consists of the source of tidal floods and their preventive measures, distance to water bodies, and accessibility.

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Section: Analytical Hierarchy Process (Ahp)mentioning

confidence: 99%

Vulnerability assessment of residential buildings to tidal flood hazards in Sriwulan Village, Sayung District, Demak Regency

Afifah

Hizbaron

2020

E3S Web Conf.

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“…To overcome these weaknesses, our proposed model is based on simplified ELCA, EcLCA, and SLCA methods. The simplified life cycle assessment was proposed by Ng C.Y [17] as a rough-cut LCA in order to address the complexity of the full LCA and to obtain the environmental performance of the desired product with the available data. Then, our idea is to connect these results to a multi-leveled fuzzy Analytic Network Process [7] [8] [9] for decision support.…”

Section: Problem Statement and Motivationmentioning

confidence: 99%

A Multi-leveled ANP-LCA Model for the Selection of Sustainable Design Options

Sansa¹,

Badreddine²,

Romdhane³

2017

Product Lifecycle Management and the Industry of the Future

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The aim of this paper is to propose a new model for the selection of sustainable design options. This model is based on the environmental, the economic, and the social life cycle assessments. It deals with the uncertainties and the imprecisions due to the technological choices and their potential impacts since early design phase of the product. The proposed model is based on four principles, namely: Early integration, life cycle thinking, functionality thinking, and the multi-criteria concept. A case study is presented to validate the applicability of the proposed model on the design of batteries.

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“…Evaluating the green degree of manufacturing process is one of key technologies in realizing green manufacturing. Some effective evaluation methods were put forward, such as life cycle assessment (LCA), analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) [1][2][3][4][5][6]. But in practical application, these methods are easy to occur the complicated evaluation process, long cycle, depending on subjective judgment and other problems, so that the effectiveness and practicability of the evaluation results become poor.…”

Section: Introductionmentioning

confidence: 99%

Sample Classification Method for Green Process Evaluation Based on Kernelized Fuzzy C-means Clustering

Wang¹,

Xiu²

2017

dtetr

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Abstract. The evaluation sample data of green process have multi-dimensional characteristic, unknown structure, and great dimensional difference. Therefore, the high-quality evaluation sample classification is difficult, when the evaluation is operated by machine learning method. A novel kernelized fuzzy C-means algorithm is proposed in order to achieve the reasonable classification of the samples. Kernelized fuzzy C-means clustering is improved by using the penalty factor; subtraction clustering is applied to enhance the accuracy of clustering; the PBMF index is used as classification condition to obtain the optimal classification number. The experimental results show that this algorithm has good validity and robustness. When the proposed algorithm is applied to classify evaluation samples of green process, the results indicate that the optimal classification of evaluation sample can be implemented effectively.

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Evaluation of Design Alternatives' Environmental Performance Using AHP and ER Approaches

Cited by 35 publications

References 17 publications

Vulnerability assessment of residential buildings to tidal flood hazards in Sriwulan Village, Sayung District, Demak Regency

Vulnerability assessment of residential buildings to tidal flood hazards in Sriwulan Village, Sayung District, Demak Regency

A Multi-leveled ANP-LCA Model for the Selection of Sustainable Design Options

Sample Classification Method for Green Process Evaluation Based on Kernelized Fuzzy C-means Clustering

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