Supplier selection for development of petroleum industry facilities, applying multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS with flexible entropy weighting

Wood, David A.

doi:10.1016/j.jngse.2015.12.021

Cited by 108 publications

(44 citation statements)

References 36 publications

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“…The different papers that used the hybrid fuzzy TOPSIS method for the supplier selection problem are those of: Chen et al (2005Chen et al ( , 2006, Boran et al (2009), Onüt et al (2009), Razmi et al (2009b), Guneri et al (2009) 2015and Wood (2016).…”

Section: Single-criterion Synthesis Approachmentioning

confidence: 99%

A systematic review on supplier selection and order allocation problems

Aouadni

Rebaï

2019

J Ind Eng Int

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The supplier selection and order allocation are two key strategic decisions in purchasing problem. The review presented in this paper focuses on the supplier selection problems (SSP) and order allocation from year 2000 to 2017 in which a new structure and classification of the existing research streams and the different MCDM methods and mathematical models used for SSP will be presented. The review was examined in three aspects: the summaries of the existing evidence concerning the problems, the identification of gaps in the current research to help determine where further investigation might be needed and positioning new research activities.

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Section: Single-criterion Synthesis Approachmentioning

confidence: 99%

A systematic review on supplier selection and order allocation problems

Aouadni

Rebaï

2019

J Ind Eng Int

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“…Bushra Luzon et al [16] used the AHP method to evaluate and determine weights for selected criteria including the quality, price, delivery, service and warranty and claims, competence engineering, manufacturing facilities and capacity, financial status, performance history and geographic location. Wood et al [17] applied Multi-Criteria Decision-Making techniques including fuzzy TOPSIS with flexible entropy weights for the purpose of selecting suppliers to develop petroleum industry facilities. José Felipe Figueiredo Barata et al [18] used a Multi-Criteria Decision-Making model to rank sustainable suppliers in the oil and gas industry in Brazil.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Criteria Decision Making (MCDM) Model for Supplier Evaluation and Selection for Oil Production Projects in Vietnam

Wang

Tsai

et al. 2020

Processes

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The following research utilizes Multi-Criteria Decision Making (MCDM) in order to build a business strategy to reduce product costs, improve competitiveness, focus on production planning based on actual operating capacity and flexible adjustment according to the market, maximize the labor productivity of technology workshops, reduce costs and inventory, and focus on producing many petrochemical products and products of high economic value. Selecting the right materials supplier is of paramount importance to the success of the organization as a whole. Supplier evaluation and the selection of a suitable supplier is a complex problem in which the decision maker must consider both qualitative and quantitative factors. Multi-Criteria Decision Making Models are an effective tool used to solve complex selection issues including multiple criteria and options, especially for qualitative variables. Thus, the author proposes an MCDM model including the Supply Chain Operation Reference (SCOR) model, analytic hierarchy process (AHP) and the Data Envelopment Analysis (DEA) method to evaluate and select the optimal supplier in the oil industry. The criteria used to evaluate potential suppliers are determined through the SCOR model, the weight of all criteria are defined by the AHP model through an expert’s opinion, and DEA is used to rank providers at the final stage. After the model implementation and the results, decision-making unit DMU_01, DMU_04 and DMU_10 are shown to be the best suppliers. This research provides a Multi-Criteria Decision Making model for supplier evaluation and selection in oil production projects. This research also presents useful guidelines for supplier selection processes in other industries.

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“…This section puts forward a new programming model for calculating the weights of the attributes. Common weight calculation methods are analytic hierarchy process (AHP) [24,25] and entropy measures [26,27] which determine weights when the information is completely unknown. Since the information about each attribute is partially known, a programming model is an effective way of using the information to calculate the weight values.…”

Section: Programming Model For Attribute Weight Calculationmentioning

confidence: 99%

Scientific Decision Framework for Evaluation of Renewable Energy Sources under Q-Rung Orthopair Fuzzy Set with Partially Known Weight Information

et al. 2019

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As an attractive generalization of the intuitionistic fuzzy set (IFS), q-rung orthopair fuzzy set (q-ROFS) provides the decision makers (DMs) with a wide window for preference elicitation. Previous studies on q-ROFS indicate that there is an urge for a decision framework which can make use of the available information in a proper manner for making rational decisions. Motivated by the superiority of q-ROFS, in this paper, a new decision framework is proposed, which provides scientific methods for multi-attribute group decision-making (MAGDM). Initially, a programming model is developed for calculating weights of attributes with the help of partially known information. Later, another programming model is developed for determining the weights of DMs with the help of partially known information. Preferences from different DMs are aggregated rationally by using the weights of DMs and extending generalized Maclaurin symmetric mean (GMSM) operator to q-ROFS, which can properly capture the interrelationship among attributes. Further, complex proportional assessment (COPRAS) method is extended to q-ROFS for prioritization of objects by using attributes' weight vector and aggregated preference matrix. The applicability of the proposed framework is demonstrated by using a renewable energy source prioritization problem from an Indian perspective. Finally, the superiorities and weaknesses of the framework are discussed in comparison with state-of-the-art methods.Sustainability 2019, 11, 4202 2 of 21 inferred from their analysis that India has a high scope for renewable energy sources and it can effectively manage energy crisis by proper planning and management. Recently, Mardani et al. [4] conducted a detailed analysis on the use of multi-attribute group decision-making (MAGDM) methods for solving energy management problems, and it can be inferred from the analysis that energy source evaluation and selection can be effectively solved by using MAGDM perspectives. Furthermore, there is uncertainty in the process of selection, which can be effectively managed by using fuzzy sets and its variants [5]. Baek and Lee et al. [6] proposed a new design strategy for optimal selection of renewable energy system (RES) in buildings. Gonzalez et al. [7] presented a conceptual model to understand the relationship among different factors that correspond to the sustainability and acceptance of RES projects. Cavallaro et al. [8,9] presented decision frameworks under intuitionistic fuzzy context to rationally select solar-hybrid power plants.Motivated by these claims, in this paper, we propose a new decision framework for rational prioritization of renewable energy sources. The preference information used here is q-rung orthopair fuzzy set (q-ROFS) [10], which is a powerful generalization of the intuitionistic fuzzy set (IFS) [11] and Pythagorean fuzzy set [12]. q-ROFS provides a wider window to decision makers (DMs) for preference elicitation by relaxing the constraint (sum of the degree of membership and non-membership less than or equal to...

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Supplier selection for development of petroleum industry facilities, applying multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS with flexible entropy weighting

Cited by 108 publications

References 36 publications

A systematic review on supplier selection and order allocation problems

A systematic review on supplier selection and order allocation problems

Multi-Criteria Decision Making (MCDM) Model for Supplier Evaluation and Selection for Oil Production Projects in Vietnam

Scientific Decision Framework for Evaluation of Renewable Energy Sources under Q-Rung Orthopair Fuzzy Set with Partially Known Weight Information

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