On a sustainability interval index and its computation through global optimization

Conner, Jeremy A.; Phillis, Yannis A.; Manousiouthakis, Vasilios I.

doi:10.1002/aic.12777

Cited by 6 publications

(13 citation statements)

References 12 publications

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“…This study aims to develop an SII based on the work of Conner et al, 7 and the developed method in this study can fill in the abovementioned two gaps. In other words, they can incorporate the preferences of numerous stakeholders and address the decision-making matrix composed by multiple types of data for multiactor life cycle sustainability ranking of industrial systems under hybrid information.…”

Section: It Lacks the Mcdm Methods Which Can Address The Decision-makimentioning

confidence: 99%

“…The preliminary of fuzzy numbers and interval numbers were presented in the Supporting Information based on the works of Conner et al, 7 Cheng and Lin, 17 Pedrycz and Gomide, 18 Zimmermann, 19 Junior et al, 20 Zhang et al, 21 Bohlender and Kulisch, 22 Liu and Huang 23 and Dymova et al 24…”

Section: Preliminarymentioning

confidence: 99%

“…However, the data with respect to some soft criteria (i.e., technology maturity, technology innovation and social acceptability) cannot be determined directly. The fuzzy scoring approach is employed to determine the relative performances of these alternative chemical processes with respect to the soft criteria suppose that there are a total of M alternatives to be assessed with respect to a soft criterion, and K experts are invited to participate in the evaluation process, each of the experts will be asked to use the linguistic terms including extremely poor (EP), very poor (VP), poor (P), fair (F), good (G), very good (VG), and extremely (EG) to rate these alternative chemical processes, and these linguistic terms correspond to (0,0,1), (1,1,3), (1,3,5), (3,5,7), (5,7,9), (7,9,10), and (9,10,10), respectively. 28 Assume that the score of the i-th alternative with respect to a criterion determined by the k-th expert isx j i,k = x L,j i,k x M,j i,k x U,j i,k , then, the score of the i-th alternative with respect to a criterion can be determined by Equation (1).…”

Section: Criteria System For Sustainability Assessmentmentioning

confidence: 99%

“…performances of the alternatives with respect to the soft criteria, and they correspond to the triangular fuzzy numbers (0,0,1), (1,1,3), (1,3,5), (3,5,7), (5,7,9), (7,9,10), and (9,10,10), respectively. 35 There are a total of K decision-makers, denotes the data of the i-th alternative with respect to the j-th criterion which is a soft criterion bỹ…”

Section: Multicriteria Decision Analysis Under Hybrid Informationmentioning

confidence: 99%

“…Phillis and Andriantiatsaholiniaina 5 proposed the use of fuzzy logic to assess sustainability. Conner et al 6,7 presented the sustainability-interval-index (SII) for sustainability assessment employing fuzzy logic, interval analysis, and global optimization concepts. Phillis et al 8 provided a review of this system of systems approach for sustainability assessment, within which there are numerous references about fuzzy logic based approaches for sustainability assessment.…”

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confidence: 99%

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Industrial system prioritization using the sustainability‐interval‐index conceptual framework with life‐cycle considerations

Ren

Shen

et al. 2020

AIChE Journal

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This study aims to develop a sustainability-interval-index (SII) conceptual framework with life-cycle considerations which can incorporate the opinions/preferences of multiple stakeholders in the complex decision-making processes and address the decision-making matrix composed by multiple types of data for multiactor life cycle ranking of industrial systems. The multiactor fuzzy best-worst method which allows multiple groups of stakeholders to use fuzzy numbers to express their opinions and preferences was developed for determining the weights of the indicators in life cycle sustainability assessment. A multicriteria decision-making method under hybrid information was developed for addressing the decision-making matrix composed by multiple types of data. Five hydrogen production pathways were studied, and the results reveal that the developed SII is feasible for sustainability ranking of industrial systems in life cycle perspective. K E Y W O R D S best-worst method, life cycle sustainability assessment, multicriteria decision-making, sustainability 1 | INTRODUCTION The concept of sustainability or sustainable development, which emphasizes the harmonious development of economy, environment, and society simultaneously, has drawn more and more attentions of the stakeholders of industrial systems. Life cycle analysis methods, which broaden the horizons from a single production process to the scale of the entire industry chain, greatly extend people's perception of the impact of industrial processes. In order to investigate the sustainability of industrial systems, the idea of combining sustainability and life cycle thinking was proposed and evolved into the life cycle sustainability assessment (LCSA) method. Sustainability assessment consists of three main pillars: economic, environmental and social. Kloepffer 1 suggested in a conceptual formula: LCSA = LCA + LCC + SLCA. LCSA has three separate life cycle based methods: life cycle assessment (LCA), life cycle costing (LCC) and social life cycle analysis (SLCA). LCSA is a transdisciplinary integration framework of models rather than a model in itself, 2 wherein, (a) LCA is the compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle 3 ; (b) LCC is the logical counterpart of LCA for the economic assessment, LCC surpasses the purely economic cost calculation by taking into account the use-and end-of-life phases and hidden costs; and (c) the key point of SLCA is how to combine social indicators with functional units of product systems using qualitative and semi-quantitative approaches. 1 Previous investigations about LCSA are usually the calculations and comparisons of single or multiple criteria for a product or technology under the same dimension. The three separate life cycle based

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Section: It Lacks the Mcdm Methods Which Can Address The Decision-makimentioning

confidence: 99%

Section: Preliminarymentioning

confidence: 99%

Section: Criteria System For Sustainability Assessmentmentioning

confidence: 99%

Section: Multicriteria Decision Analysis Under Hybrid Informationmentioning

confidence: 99%

mentioning

confidence: 99%

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Industrial system prioritization using the sustainability‐interval‐index conceptual framework with life‐cycle considerations

Ren

Shen

et al. 2020

AIChE Journal

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Multiactor multicriteria decision making for life cycle sustainability assessment under uncertainties

Ren

Dong

et al. 2018

AIChE Journal

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This article aims at developing a generic multiactor multicriteria decision making (MAMCDM) method for life cycle sustainability assessment (LCSA) of industrial systems under uncertainties, which can help multiple stakeholders/decision-makers to prioritize the alternative industrial systems in a group decision-making approach. The interval bestworst method, which can address the ambiguity, vagueness and hesitations existing in human's judgments, was developed for determining the weight of the criteria in LCSA. The consensus convergence model was developed for aggregating the relative importance of each criterion determined by different stakeholders/decision-makers into an interval weight. Afterward, a novel multicriteria decision-making method which can address the decision-making matrix with interval numbers was developed to prioritize industrial systems under data uncertainties. An illustrative case has been studied by the developed model, and it reveals that the developed model allows multiple stakeholders/decision-makers to participate in the decision-making processes and prioritize industrial systems accurately by using interval numbers.

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Sustainability Over Sets

Manousiouthakis

Jorat

2017

Env Prog and Sustain Energy

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In this work, the novel concept of “Sustainability Over Set” (SOS) is introduced. This novel concept provides broad flexibility in incorporating human input into system sustainability assessment. In addition, the new concept is shown to be readily quantifiable, thus enabling definitive (yes or no) and reproducible answers to the question “is a system sustainable?”. The concept of positive invariant sets plays a key role in this quantification process, leading to simple mathematical criteria for sustainability assessment. Following the SOS introduction, two illustrative case studies are presented, one of which focuses on sustainability assessment of a biological reactor system similar to those commonly used for waste treatment. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1093–1100, 2018

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On a sustainability interval index and its computation through global optimization

Cited by 6 publications

References 12 publications

Industrial system prioritization using the sustainability‐interval‐index conceptual framework with life‐cycle considerations

Industrial system prioritization using the sustainability‐interval‐index conceptual framework with life‐cycle considerations

Multiactor multicriteria decision making for life cycle sustainability assessment under uncertainties

Sustainability Over Sets

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