Decision making in energy planning: the ELECTRE multicriteria analysis approach compared to a FUZZY-SETS methodology

Beccali, Marco; Cellura, Maurizio; Ardente, Davide

doi:10.1016/s0196-8904(98)00053-3

Cited by 124 publications

(61 citation statements)

References 2 publications

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“…In the last few decades, the improved ELECTRE methods such as the ELEC-TRE-II, ELECTRE-III, ELECTRE-IV, ELECTRE-TRI, and ELECTRE-IS [23][24][25][26][27] have been proposed in succession and widely applied in certain types of real world problems including engineering, economics, management, and environment. Although several decades have passed since the birth of the first ELECTRE method, research on ELECTRE family method is still active and evolving today [28][29][30][31]. All ELECTRE methods belong to the family of outranking methods [32], one of the classic families of methods within MCDA.…”

Section: Electre Methodsmentioning

confidence: 99%

A Decision Model for Emergency Warehouse Location Based on a Novel Stochastic MCDA Method: Evidence from China

Feng

et al. 2017

Mathematical Problems in Engineering

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China is one of the disaster-prone countries in the world. Constructing a rapid and effective relief logistic system is important for disaster-responding at country level. Strategic prepositioning of emergency items, especially the decision of appropriate emergency warehouses location, has significant impacts on rapid disaster response to ensure sufficient relief supplies. The emergency warehouse location decision is a complex problem, where a wide variety of criteria need to be considered and the preference information of decision makers (DMs) may be imprecise or even absent. In this paper, we identify key effectiveness-oriented criteria used to evaluate the alternative emergency warehouse locations and make an attempt to propose a new multicriteria ranking method to solve the problem of inaccurate or uncertain weight information based on stochastic pairwise dominant relations and the pruning procedure of ELECTRE-II method. The proposed method extends the conventional ELECTRE-II method by incorporating inaccurate information and broadens its application to emergency warehouse location field. The feasibility and applicability of the proposed method are illustrated with a simulated example.

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Section: Electre Methodsmentioning

confidence: 99%

A Decision Model for Emergency Warehouse Location Based on a Novel Stochastic MCDA Method: Evidence from China

Feng

et al. 2017

Mathematical Problems in Engineering

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“…Table 1 shows the most important MCDM methods used for assessing energy policy and management: AHP; PROMETHEE; ELECTRE; and TOPSIS (Pohekar and Ramachandran 2004). Beccali et al (1998) introduced a methodological tool able to organize the large set of variables of several specific assessments that help the decision maker in a complex problem. The authors used the ELECTRE methods to decide upon involving the use or non-use of fuzzy set concepts on the Italian island of Sardinia for renewable energy diffusion strategy planning.…”

Section: Related Workmentioning

confidence: 99%

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

Afsordegan

Sánchez

Agell

et al. 2016

Int. J. Environ. Sci. Technol.

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Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be represented by numerical values, in particular in energy analysis and planning. In this paper, a modified TOPSIS method for multi-criteria group decision-making with qualitative linguistic labels is proposed. This method addresses uncertainty considering different levels of precision. Each decision maker's judgment on the performance of alternatives with respect to each criterion is expressed by qualitative linguistic labels. The new method takes into account linguistic data provided by the decision makers without any previous aggregation. Decision maker judgments are incorporated into the proposed method to generate a complete ranking of alternatives. An application in energy planning is presented as an illustrative case example in which energy policy alternatives are ranked. Seven energy alternatives under nine criteria were evaluated according to the opinion of three environmental and energy experts. The weights of the criteria are determined by fuzzy AHP, and the alternatives are ranked using qualitative TOPSIS. The proposed approach is compared with a modified fuzzy TOPSIS method, showing the advantages of the proposed approach when dealing with linguistic assessments to model uncertainty and imprecision. Although the new approach requires less cognitive effort to decision makers, it yields similar results.

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“…An analysis of various technological factors may take into account the type of proposed energy solution (conventional and/or renewable energy technologies); its efficiency and suitability in terms of meeting energy demands (Georgopoulou et al, 1997); the maturity of the energy technology considered (Beccali et al, 1998); its applicability (Georgopoulou et al, 2003); its dependence of fossil fuels (Kablan, 1997) and the availability of required fuel resources (Borroto et al, 1998); and the disadvantages and uncertainties related to the construction process of a power generation facility (Angel y Smith, 2000), among others. Additional technical criteria considered may be the state of art of technologies in terms of their application and conditions under which they were employed; the technical resources of a site, such as wind speed, solar radiation, and availability of biomass; operating characteristics, including local capacity to operate and maintain the systems; and level of local replicability (Biswas et al, 2001).…”

Section: Single-criterionmentioning

confidence: 99%

A Multi-criteria Decision-Support Approach to Sustainable Rural Energy in Developing Countries

Cherni

Kalas

2010

Handbook on Decision Making

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Numerous models have been developed to aid in the decision making process to identify the most suitable energy provision options for a given community or area. Some models focus strictly on one key planning aspect, such as cost or technology (single-criteria decision analysis), while other models take multiple criteria into consideration, such as cost and technology, social, human and environmental factors (multi-criteria analysis). This chapter aims to show that the inclusion of multiple technical and non-technical criteria can lead to more sustainable development outcomes. To do so, it provides a comparison between several single factor and multi-criteria models, highlighting their applications and limitations in the context of rural energy planning in developing countries. This is followed by a discussion of the factors that should be considered to ensure optimal service provision,, long-term sustainability of rural electrification projects and poverty alleviation. The subsequent section introduces and analyses the components of the Sustainable Rural Energy Decision Support System (SURE-DSS) approach and methodology. The novelty of the SURE tool lies in its objective to match rural community's energy needs in developing countries to appropriate technologies and thereby improve livelihoods and project sustainability. The chapter explains the approach and illustrates the tool's application through a case study in Colombia.

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Decision making in energy planning: the ELECTRE multicriteria analysis approach compared to a FUZZY-SETS methodology

Cited by 124 publications

References 2 publications

A Decision Model for Emergency Warehouse Location Based on a Novel Stochastic MCDA Method: Evidence from China

A Decision Model for Emergency Warehouse Location Based on a Novel Stochastic MCDA Method: Evidence from China

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

A Multi-criteria Decision-Support Approach to Sustainable Rural Energy in Developing Countries

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