Multi-criteria Group Decision Support with Linguistic Variables in Long-term Scenarios for Belgian Energy Policy

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Multi-criteria Group Decision Support with Linguistic Variables in Long-term Scenarios for Belgian Energy Policy
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    Multi-criteria Group Decision Support with Linguistic Variables in Long-term Scenarios for Belgian Energy Policy Da Ruan 1   (Expertise Unit of Society and Policy Support Belgian Nuclear Research Centre (SCK•CEN) Boeretang 200, 2400 Mol, Belgium druan@sckcen.be ) Jie Lu (Lab of Decision Systems and e-Service Intelligence, Center of Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology University of Technology, Sydney (UTS) PO Box 123, Broadway, NSW 2007, Australia  jielu@it.uts.edu.au) Erik Laes (Unit Transition Energy & Environment (TEM) Flemish Institute for Technological Research (VITO) Boeretang 200, B-2400 Mol, Belgium erik.laes@vito.be) Guangquan Zhang, Jun Ma   (Lab of Decision Systems and e-Service Intelligence, Center of Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology University of Technology, Sydney (UTS) PO Box 123, Broadway, NSW 2007, Australia {zhangg, junm}@it.uts.edu.au) Gaston Meskens (Expertise Unit of Society and Policy Support Belgian Nuclear Research Centre (SCK•CEN) Boeretang 200, 2400 Mol, Belgium gmeskens@sckcen.be) Abstract:  Real world decisions often made in the presence of multiple, conflicting, and incommensurate criteria. Decision making requires multiple perspectives of different individuals as more decisions are made now in groups than ever before. This is particularly true when the decision environment becomes more complex such as sustainability policies study in environmental and energy sectors. Group decision making processes judgments or solutions for decision problems based on the input and 1  Corresponding author  Journal of Universal Computer Science, vol. 15, no. 1 (2010), 103-120submitted: 1/2/09, accepted: 15/10/09, appeared: 1/1/10  ©  J.UCS    feedback of multiple individuals. Multi-criteria decision and evaluation problems at tactical and strategic levels in practice involve fuzziness in terms of linguistic variables vis-à-vis criteria, weights, and decision maker judgments. Relevant alternatives or scenarios are evaluated according to a number of desired criteria. A fuzzy multi-criteria group decision software tool is developed to analyze long-term scenarios for Belgian energy policy in this paper. Keywords : Fuzzy numbers; Multi-criteria decision making (MCDM); Linguistic variables; Group decision support; Energy policy, Evaluation model Categories: F.4.3, J.5, H.5.3, M.4 1 Introduction The Belgian parliament in 2003 enacted a law to progressively phase out existing nuclear power plants. Decision has caused contestation among a number of historically active social groups in the energy policy debate. Referring to this relatively controversial climate, the research reported in [Laes, 2006] stretches the scope of the debate outside the boundaries of political (parliamentary) decision making. Among many interesting issues related to nuclear energy and sustainable development, Laes [Laes, 2006] attempted to shed some light on the question whether nuclear electricity generation can contribute to the transition towards a sustainable energy future for Belgium, and, if so, under which conditions. Laes argued that scientific contributions to sustainable development do not follow the linear   procedure from empirical knowledge production to policy advice. Instead, they consist of  problem-oriented combinations of explanatory, orientation- and action-guiding knowledge. Society and policy makers not only have to be  provided   with action-guiding knowledge, but also with an awareness of the manner in which this knowledge is to be interpreted, and where the inevitable uncertainties lie. Since the sustainability question is inherently multi-dimensional, participation of social groups is an essential element of a strategy aimed at sustainable development. Multi-criteria decision support provides a platform to accommodate a process of arriving at a judgment or a solution for the sustainability question based on the input and feedback of multiple individuals. At the same time in practice, multi-criteria decision problems at tactical and strategic levels often involve fuzziness in their criteria and decision makers’  judgments. Due to the multi-dimensional nature of the sustainability question, we  believe that the evaluation of strategic policy options has to be based on procedures that explicitly recognize the integration of a broad set of (possibly conflicting) points of view. Multi-criteria evaluation techniques can in principle provide an appropriate  policy framework for setting long-term strategic priorities [Laes, 2006]. Multi-criteria decision making (MCDM) with linguistic variables, commonly known as fuzzy multi-criteria decision making (FMCDM), has been one of the fastest growing areas in decision making and operations research during the last three decades [Marimin et al, 1998, Nishizaki et al, 1994, Yager and Zadeh, 1992, Zimmermann, 1987]. The motivation for the development of FMCDM is the large number of criteria that decision makers are expected to incorporate in their actions 104  Ruan D., Lu J., Laes E., Zhang G., Ma J., Meskens G.: Multi-criteria ...   and the difficulty of expressing decision makers' opinions by crisp values in practice [Zadeh, 1975a, 1975b, 1975c]. Group decision making takes into account how experts work together in reaching a decision. Uncertain factors often appear in a group decision process, namely with regard to decision makers' roles (weights), preferences (scores) for alternatives (scenarios), and judgments (weights) for criteria (indicators) [Lu et al, 2007, Marimin et al, 1998]. In this paper, we argue in favor of the use of a fuzzy-logic based multi-criteria group decision support tool for long-term scenarios of Belgian energy policy. The paper is organized as follows. In Section 2, we briefly outline the problem statement of long-term scenarios of Belgian energy policy. In Section 3, we present a fuzzy multi-criteria group decision making (FMCGDM) algorithm. In Section 4, we illustrate an application of the FMCGDM algorithm on a case-study of Belgian long-term energy policy support. In Section 5, we further compare the result obtained from the proposed FMCGDM method with the one from earlier methods from [Laes, 2006]. Finally in Section 6, we conclude the use of the FMCGDM algorithm in the context of Belgian sustainable energy policy. 2 Problem Statement of Long-term Scenarios for Belgian Sustainable Energy Policy This paper aims to discuss the methodological issues of multi-criteria decision support in the context of sustainable energy policy. For details about the substantive results of the Belgian case, we refer to [Laes, 2006]. The decision criteria used in the multi-criteria decision exercise were derived mainly from the substantive results of the Belgian case [Laes, 2006] and related  publications and policy documents in the field of sustainable energy policy. However, it is important to note that these criteria are a technical translation  of the preferences and needs of those experts or stakeholders (who participated in the multi-criteria decision exercise), operated by the research team within [Laes, 2006]. Such translation is a necessity since the technical formulation of decision criteria needs to show properties such as non-redundancy , legibility , etc. which cannot simply be extracted   from the rough material contained in interviews [Bouyssou, 1990]. Decision criteria were subsequently structured into a combined value tree . This combined value tree  includes four important issues (high-level criteria): i) Environmental and human health & safety, ii) Economic welfare, iii) Social, political, cultural and ethical needs, and iv) Diversification. Just for the first dimension (see Figure 1), seven aspects were defined (intermediate-level criteria): 1) Air pollution, 2) Occupational health, 3) Radiological health impacts, 4) Aesthetic, 5) Other environmental impacts, 6) Resource use, and 7) Other energy related pressures. For the first dimension alone, each aspect had one or more low-level criteria. 105  Ruan D., Lu J., Laes E., Zhang G., Ma J., Meskens G.: Multi-criteria ...    Figure 1: Structured value tree for 'Environmental & human health and safety' issues As reported in [Laes et al, 2008]: One crucial part of decision-analytic methods is how the decision problem under scrutiny is constructed, and as a consequence, the alternatives for solving the problem. In the context of a long-term policy for sustainable energy development, clearly, there is no single  decision involved, but rather a set of interlinked decisions, none of which taken on its own constitutes the  policy, but which in combination produces a process which we could describe as a strategy . Nevertheless, in order to use a decision-analytic procedure, we need to represent clearly distinctive alternatives for action  in a way that would allow  participants in the exercise to choose among them. Hence, a possible conflict emerges  between the complexity of the real world   and the simplicity  required for the purposes of decision-analytic modeling. In principle, there is no right   solution to this dilemma; one can only try to propose an acceptable (pragmatic) solution [Guitouni and Martel, 1998]. For the scenarios/alternatives, Laes [Laes, 2006] used two different worlds  (assumptions about how the market, political institutions and consumers behave): the  Market   world (M) and the  Rational Perspective  world (R). M denotes higher economic discount rates, lower penetration levels for renewable energy and less 106  Ruan D., Lu J., Laes E., Zhang G., Ma J., Meskens G.: Multi-criteria ...    possibilities for energy saving; R indicates lower discount rates, higher penetration levels for renewable and more possibilities for energy-saving behaviour. The codes each describe the dominant energy supply strategy used within a  particular world   (all scenarios assume that a reduction of greenhouse gases will be imposed upon energy policy). Basically, the possibilities are nuclear, carbon capture & storage, import of electricity (up to 30%), and renewable & cogeneration. Each scenario looks at what happens if one suppresses one strategy, e.g., no nuclear, low carbon capture & storage, no import. This is described by the letter codes: P - nuclear  phase out; LCS - low carbon capture and storage; I - import of electricity. So the scenario MPLCS is a scenario using the  Market   assumptions, and assuming a nuclear  phase out, no import and low potential for carbon capture & storage (e.g., investments will be necessarily placed in renewable & cogeneration). RLCS uses the  Rational Perspective  assumptions, and assumes a low potential for carbon capture & storage and no import (so this scenario will invest in nuclear). In this study, we assume eight scenarios ( S  1 , S  2 , …, S  8 ) as (MLCS, MPCS, MPLCS, MPLCSI, RLCS, RPCS, RPLCS, RPLCSI). There are many ways to evaluate this policy option study. Standard multi-criteria decision support and group decision support systems are typically suitable for such a study [Chen, 2000, Dubois et al, 2001, Zimmermann, 1987]. Due to the complexity of this study, different experts will have different views under various uncertain information for different scenarios ( S  1 , S  2 , …, S  8 ). Expert views are often expressed in certain linguistic variables and some undetermined values during the evaluation  procedure. In the srcinal multi-criteria exercise in [Laes, 2006], Laes used only crisp values for weights and criterion scores. In the current paper, we have softened those crisp values into certain fuzzy numbers that better reflect perception based views from experts. Hence the integration of multi-criteria decision making, group decision making and fuzzy logic systems is recommended to carry out for this study. By giving a rational-political group decision model [Lu et al, 2007, Marimin et al, 1998], we mainly identify three uncertain factors involved in a group decision-making process: decision makers’ roles (weights), preferences (scores) for alternatives (scenarios), and  judgments (weights) for criteria. The next section presents an FMCGDM algorithm to deal with the three uncertain factors to a multi-level, multi-criteria decision to generate a group satisfactory decision. The solution is in the most acceptable degree of the group for this study. With the help of the FMCGDM algorithm, a software package designed to assist multi-criteria decision analysis under uncertainties, a long-term scenarios study for Belgian energy policy has being carried out as a result of the cooperation between the Belgian Nuclear Research Centre (SCK•CEN) and University of Technology, Sydney (UTS).   3 Fuzzy Multi-Criteria Group Decision Making Algorithm In this section, a proposed FMCGDM algorithm, based on the previous study [Lu et al, 2006, Zhang and Lu, 2003] is developed for evaluating different long-term scenarios of Belgian energy policy. 107  Ruan D., Lu J., Laes E., Zhang G., Ma J., Meskens G.: Multi-criteria ...
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