Lazim Abdullah

Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia

Energy consumption for developing countries is sharply increasing due to the higher economic growth due to industrialisation along with population growth and urbanisation. The increasing demand of energy leads to global energy crisis. Selecting the best energy technology and conservation requires both quantitative and qualitative evaluation criteria. The fuzzy set-based approach is one of the well-known theories to handle fuzziness, uncertainty in decision-making and vagueness of information. This paper proposes a new method of intuitionistic fuzzy analytic hierarchy process (IF-AHP) to deal with the uncertainty in decision-making. The new IF-AHP is applied to establish a preference in the sustainable energy planning decision-making problem. Three decision-makers attached with Malaysian government agencies were interviewed to provide linguistic judgement prior to analysing with the new IF-AHP. Nuclear energy has been decided as the best alternative in energy planning which provides the highest weight among all the seven alternatives.

A new preference scale mcdm method based on interval-valued intuitionistic fuzzy sets and the analytic hierarchy process

The intuitionistic fuzzy analytic hierarchy process (IF-AHP), in which intuitionistic fuzzy numbers are utilized in defining decision makers’ linguistic judgment, has been used to solve various multi-criteria decision-making problems. Previous theories have suggested that interval-valued intuitionistic fuzzy numbers (IVIFN) with hesitation degree can act as alternative fuzzy numbers that can handle vagueness and uncertainty. This paper proposes a new preference scale in the framework of the interval-valued intuitionistic fuzzy analytic hierarchy process (IVIF-AHP). The comparison matrix judgment is expressed in IVIFN with degree of hesitation. The proposed new preference scale concurrently considers the membership function, the non-membership function and the degree of hesitation of IVIFN. To define the weight entropy of the aggregated matrix of IVIFN, a modified interval-valued intuitionistic fuzzy weighted averaging is proposed, by considering the interval number of the hesitation degree. Three multi-criteria decision-making problems are used to test the proposed method. A comparison of the results is also presented to check the feasibility of the proposed method. It is shown that the ranking order of the proposed method is slightly different from that of the other two methods because of the inclusion of the hesitation degree in defining the preference scale.

A new preference scale of intuitionistic fuzzy analytic hierarchy process in multi-criteria decision making problems

Analytic Hierarchy Process AHP is a tool of decision making technique which complies with complex decision making in any kind of situations. AHP deals with structuring the hierarchical layer to perform the preference judgement of each criterion and alternatives in multi-criteria decision making MCDM problems. The sequence of AHP structure unfortunately lack of certainty as the evaluation consists of vagueness. Thus, the theory of intuitionistic fuzzy sets IFS is integrated with AHP method to deal with these uncertainty and vagueness of the AHP preference judgement. The aim of this paper is to propose a new intuitionistic fuzzy analytic hierarchy process IF-AHP method characterised by new preference scale of pair-wise comparison matrix measurement. The new preference scale considers the degree of hesitation of IFS in expressing the conversion of consistency to a triangular intuitionistic fuzzy numbers TIFNs. The values of hesitation degree are averaged to test consistency of matrix judgment. The intuitionistic fuzzy weighted averaging IFWA is utilized to aggregate the matrix assessment of the decision makers DMs into a group opinion. Modified intuitionistic fuzzy entropy is used to obtain the entropy weights of each criterion and alternatives. Three MCDM problems were used to illustrate the proposed method. It is found the ranking of MCDM problems using the proposed method were slightly inconsistent with the original ranking.

Neural Network Training Algorithm for Carbon Dioxide Emissions Forecast: A Performance Comparison

Artificial neural network with many types of algorithms is known as an efficient tool in forecasting as it is able to handle nonlinearity behaviour of data. This paper investigates the performances of Levenberg-Marquardt and gradient descent algorithms of back propagation neural networks carbon dioxide emissions forecast. The inputs for the model were selected and the ANNs were trained using the Malaysian data of energy use, gross domestic product per capita, population density, combustible renewable and waste and carbon dioxide intensity. The forecasting performances were measured using coefficient of determination, root means square error, mean absolute error, mean absolute percentage error, number of epoch and elapsed time. Comparison between these algorithms show that the Levenberg-Marquardt was outperformed the gradient descent in carbon dioxide emissions forecast.

A Linear Assignment Method of Simple Additive Weighting System in Linear Programming Approach Under Interval Type-2 Fuzzy Set Concepts for MCDM Problem

The ranking phase is valuable to examines the final alternative rankings of decision making problems. Based on simple additive weighting (SAW) and linear programming (LP) within the context of interval type-2 fuzzy sets (IT2 FSs), we develop a linear assignment method to produce the final ranking order of all alternatives for interval type-2 fuzzy TOPSIS (IT2 FTOPSIS) method. A numerical example is used to check the efficiency and applicability of the proposed method. The results shows consistent outcomes of the decision making process. Thus, the proposed method offers an alternative, user-friendly method that is robust in the decision making framework.

A New Aggregating Phase for Interval Type-2 Fuzzy TOPSIS Using the ELECTRE I Method

Aggregating phase is considered as one of the important steps in interval type-2 fuzzy TOPSIS (IT2 FT) instead of ratings of alternatives under criteria and the importance weights of criteria and ranking of alternatives. However, some problems occur in aggregating phase of IT2 FT when it is have a large computational procedure due to the hardly defined in the second membership function. Therefore, we offer a more easier and practical in defining the new aggregating phase. Our proposed method is to establish a new aggregating phase for IT2 FT using the ELECTRE I method in the interval type-2 fuzzy set (IT2FS) concept. A numerical example is constructed to show the practicality and effectiveness of the proposed method.

A New Qualitative Evaluation for an Integrated Interval Type-2 Fuzzy TOPSIS and MCGP

Sometimes, information needed an objectively evaluation. It is hard to determine the value of some parameters because of their uncertain or ambiguous nature. However, most of the study neglected the qualitative evaluation. This paper aims to propose a new qualitative evaluation which considers three different aspects which are linguistic to crisp, the unconvinced decision and in between. This new qualitative evaluation is developed to produce an optimal preference ranking of an integrated fuzzy TOPSIS and multi-choice goal programming MCGP in interval type-2 fuzzy sets (IT2 FSs) aspects. An example is used to illustrate the proposed method. The results show that the qualitative evaluation in the new method is suitable for the integrated interval type-2 fuzzy TOPSIS and MCGP. Results are consistent with the numerical example. This new method offers a new dimension to type-2 fuzzy group decision-making environment.

A New Positive and Negative Linguistic Variable of Interval Triangular Type-2 Fuzzy Sets for MCDM

Fuzzy linguistic variable in decision making field has received significant attention from researchers in many areas. However, the existed research is given attention only in one side rather than two sides. Therefore, the aim of this paper is to introduce a new linguistic variable which considers both sides, positive and negative sides for symmetrical interval triangular type-2 fuzzy set (T2 FS). This new linguistic variable is developed in line with the interval type-2 fuzzy TOPSIS (IT2 FTOPSIS) method. Besides, a ranking value for aggregation process is modified to capture both positive and negative aspect for triangular. Then, this new method is tested using two illustrative examples. The results show that the new method is highly beneficial in terms of applicability and offers a new dimension to problem solving technique for the type-2 fuzzy group decision-making environment.

A new concept of similarity measure for IT2FS TOPSIS and its use in decision making

Multiple criteria decision making (MCDM) is widely used in ranking alternatives from a set of available alternatives with regard to relevant criteria. Fuzzy TOPSIS is the famous technique in MCDM problem. The combination of fuzzy TOPSIS and Interval Type-2 Fuzzy Set have made this technique better in handling uncertainty due to the fact IT2FS is better in handling uncertainty than Type-1 Fuzzy Set. Usually, in TOPSIS method, Euclidean distance is used. However, instead of using Euclidean distance we choose Cosine Similarity Measure (CSM) in finding the distance. Some modifications of CSM have been made to accustom with the interval type-2 fuzzy TOPSIS. In order to clarify this approach, we illustrated a solution of numerical example for supplier selection problem at the end of this paper.

Flood control project selection using an interval type-2 entropy weight with interval type-2 fuzzy TOPSIS

Flood control project is a complex issue which takes economic, social, environment and technical attributes into account. Selection of the best flood control project requires the consideration of conflicting quantitative and qualitative evaluation criteria. When decision-makers’ judgment are under uncertainty, it is relatively difficult for them to provide exact numerical values. The interval type-2 fuzzy set (IT2FS) is a strong tool which can deal with the uncertainty case of subjective, incomplete, and vague information. Besides, it helps to solve for some situations where the information about criteria weights for alternatives is completely unknown. Therefore, this paper is adopted the information interval type-2 entropy concept into the weighting process of interval type-2 fuzzy TOPSIS. This entropy weight is believed can effectively balance the influence of uncertainty factors in evaluating attribute. Then, a modified ranking value is proposed in line with the interval type-2 entropy weight. Quantitative and qualitative factors that normally linked with flood control project are considered for ranking. Data in form of interval type-2 linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. Study is considered for the whole of Malaysia. From the analysis, it shows that diversion scheme yielded the highest closeness coefficient at 0.4807. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the diversion scheme recorded the first rank among five causes.Flood control project is a complex issue which takes economic, social, environment and technical attributes into account. Selection of the best flood control project requires the consideration of conflicting quantitative and qualitative evaluation criteria. When decision-makers’ judgment are under uncertainty, it is relatively difficult for them to provide exact numerical values. The interval type-2 fuzzy set (IT2FS) is a strong tool which can deal with the uncertainty case of subjective, incomplete, and vague information. Besides, it helps to solve for some situations where the information about criteria weights for alternatives is completely unknown. Therefore, this paper is adopted the information interval type-2 entropy concept into the weighting process of interval type-2 fuzzy TOPSIS. This entropy weight is believed can effectively balance the influence of uncertainty factors in evaluating attribute. Then, a modified ranking value is proposed in line with the interval type-2 entropy weight. Quantita...