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Journal ArticleDOI

Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain

TL;DR: This paper proposes a hybrid approach that combines the revised Simos procedure, PROMETHEE methods, algorithms for constructing a group compromise ranking, and robustness analysis, and introduces and applies some original procedures based on Binary Linear Programming.
Abstract: The food sector has a prodigious focus and is constantly gaining in importance in today’s global economic marketplace. Due to an increasing global population, society faces a greater challenge for sustainable food production, quality, distribution, and food safety in the food supply chain. Adopting green supply chain management (GSCM) elements is essential for utilizing the food supply chain in an environmentally benign way. As a solution to the above challenge, the economic and green characteristics for supplier selection in green purchasing are studied in this paper. For an organization, the evaluation and selection of the green supplier is a vital issue due to several tangible and intangible criteria involved. Accordingly, we apply multiple criteria decision aiding techniques. We propose a hybrid approach that combines the revised Simos procedure, PROMETHEE methods, algorithms for constructing a group compromise ranking, and robustness analysis. At first, the revised Simos procedure is used to derive the criteria weights. Next, the PROMETHEE method is applied to rank the suppliers according to each Decision Maker׳s (DM׳s) preferences. Then, the compromise ranking is constructed to minimize the distance of the individual׳s rankings from the solution adopted by the whole group. For this purpose, we introduce and apply some original procedures based on Binary Linear Programming. Finally, the results are validated against the outcomes of robustness analysis. The applicability and efficiency of the proposed approach is endorsed with a case study in an Indian food industry.
Citations
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Journal ArticleDOI
TL;DR: An integrated methodology to address MCGDM problems based on the best-worst method (BWM) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique in an interval type-2 fuzzy environment is provided.

214 citations

Journal ArticleDOI
TL;DR: A novel model that integrates the best–worst method (BWM), modified fuzzy technique for order preference by similarity to ideal solution (TOPSIS), and fuzzy multi-objective linear programming (FMOLP) to solve problems in green supplier selection and order allocation is proposed.

188 citations


Cites methods from "Application of a novel PROMETHEE-ba..."

  • ...In the future, researchers can expand on our research by using different MADM tools (e.g., VIKOR, PROMETHEE, ELECTRE, or grey relational analysis) to select suppliers or applying heuristic methods (e.g., nondominated sorting genetic algorithm II, the particle swarm optimization algorithm, or the ant colony optimization algorithm) to solve MOLP problems, and to compare the difference and applicability with current model....

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  • ...…(Luthra et al., 2017; Sarkar et al., 2017), preference ranking organization method for enrichment evaluation (PROMETHEE) (Behzadian et al., 2010; Govindan et al., 2017; Marttunen et al., 2017) and elimination and choice translating reality (ELECTRE) (Govindan and Jepsen, 2016; Marttunen et…...

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  • ...The MADM approach of supplier evaluation can be explored using several methods, including the analytic hierarchy process (AHP) (Kumar et al., 2017), the analytic network process (ANP) (Wan et al., 2017), the best– worst method (BWM) (Rezaei et al., 2015), the decision-making trial and evaluation laboratory (DEMATEL) (Govindan et al., 2015), the technique for order preference by similarity to ideal solution (TOPSIS) (Chen, 2016), visekriterijumska optimizacija i kompromisno resenje (VIKOR) (Luthra et al., 2017; Sarkar et al., 2017), preference ranking organization method for enrichment evaluation (PROMETHEE) (Behzadian et al., 2010; Govindan et al., 2017; Marttunen et al., 2017) and elimination and choice translating reality (ELECTRE) (Govindan and Jepsen, 2016; Marttunen et al., 2017; Wan et al., 2017)....

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  • ...The modified TOPSIS was used because it does not need a series of pairwise comparisons as other MADM models (e.g., PROMETHEE)....

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  • ...The ranking of suppliers was different from the common MCDM methods (e.g. VIKOR, TOPSIS, PROMETHEE, or ELECTRE)....

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Journal ArticleDOI
TL;DR: In this article, the authors present and analyse a variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and capability maturity with big data.
Abstract: This special issue explores big data analytics and applications for logistics and supply chain management by examining novel methods, practices, and opportunities. The articles present and analyse a variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and supply chain capability maturity with big data. This editorial note summarizes the discussions on the big data attributes, on effective practices for implementation, and on evaluation and implementation methods.

162 citations

Journal ArticleDOI
TL;DR: By showing how decision making can be split into manageable and justifiable steps, it is shown how the DSSs for MCDA method recommendation can be grouped into three main clusters, which can enhance a traceable and categorizable development of such systems.
Abstract: Decision making is a complex task that involves a multitude of perspectives, constraints, and variables. Multiple Criteria Decision Analysis (MCDA) is a process that has been used for several decades to support decision making. It includes a series of steps that systematically help Decision Maker(s) (DM(s)) and stakeholders in structuring a decision making problem, identifying their preferences, and building a decision recommendation consistent with those preferences. Over the last decades, many studies have demonstrated the conduct of the MCDA process and how to select an MCDA method. Until now, there has not been a review of these studies, nor a proposal of a unified and comprehensive high-level representation of the MCDA process characteristics (i.e., features), which is the goal of this paper. We introduce a review of the research that defines how to conduct the MCDA process, compares MCDA methods, and presents Decision Support Systems (DSSs) to recommend a relevant MCDA method or a subset of methods. We then synthesize this research into a taxonomy of characteristics of the MCDA process, grouped into three main phases, (i) problem formulation, (ii) construction of the decision recommendation, and (iii) qualitative features and technical support. Each of these phases includes a subset of the 10 characteristics that helps the analyst implementing the MCDA process, while also being aware of the implication of these choices at each step. By showing how decision making can be split into manageable and justifiable steps, we reduce the risk of overwhelming the analyst, as well as the DMs/stakeholders during the MCDA process. A questioning strategy is also proposed to demonstrate how to apply the taxonomy to map MCDA methods and select the most relevant one(s) using real case studies. Additionally, we show how the DSSs for MCDA method recommendation can be grouped into three main clusters. This proposal can enhance a traceable and categorizable development of such systems.

136 citations


Cites background from "Application of a novel PROMETHEE-ba..."

  • ...management [131], ecosystem services governance [109], sensors placement [13], resilience and sustainability quantification [107,61], energy policy ranking [42], product recovery activities [9], supply chain management [67], waste recycling [66], freight selector [53], housing affordability [122], raw material supply risk assessment [87], water supply systems [149], and polluted land remediation [81]....

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Journal ArticleDOI
01 Feb 2021
TL;DR: A new group decision-making approach based on Industry 4.0 components for selecting the best green supplier by integrating AHP and TOPSIS methods under the Pythagorean fuzzy environment is developed.
Abstract: Advances in information and communication technology have created innovator technologies such as cloud computing, Internet of Things, big data analysis and artificial intelligence. These technologies have penetrated production systems and converted them smart. However, this transformation did not only affect production systems, but also differentiated supplier selection processes. In the supplier selection process, the usage of new technologies along with traditional and green criteria extensively has been investigated in recent years. This paper aims to develop a new group decision-making approach based on Industry 4.0 components for selecting the best green supplier by integrating AHP and TOPSIS methods under the Pythagorean fuzzy environment. In the proposed approach, judgments of different experts are expressed by linguistic terms based on Pythagorean fuzzy numbers. The interval-valued Pythagorean Fuzzy AHP method is utilized to determine the criteria weights. The Pythagorean Fuzzy TOPSIS method based on the distances of suppliers is applied to obtain the ranking of the suppliers and determine the most suitable one. Finally, a real case study on an agricultural tools and machinery company is presented to indicate the effectiveness and accuracy of the proposed selection approach.

132 citations

References
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Journal ArticleDOI
TL;DR: In this paper, the authors present a literature review on sustainable supply chain management taking 191 papers published from 1994 to 2007 into account, and a conceptual framework to summarize the research in this field comprising three parts.

4,760 citations

Journal ArticleDOI
TL;DR: This paper reviews, annotates, and classfies 74 related articles which have appeared since 1966 and specific attention is given to the criteria and analytical methods used in the vendor selection process.

2,089 citations

Journal ArticleDOI
TL;DR: Evidence is provided that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.

2,000 citations

Journal ArticleDOI
TL;DR: In this article, the Promethee methods, a new class of outranking methods in multicriteria analysis, have been proposed, whose main features are simplicity, clearness and stability.

1,996 citations

Posted Content
TL;DR: The main features of the Promethee methods are simplicity, clearness and stability, a new class of outranking methods in multicriteria analysis, and some further problems are discussed.
Abstract: Abstract In this paper, we present the Promethee methods, a new class of outranking methods in multicriteria analysis. Their main features are simplicity, clearness and stability. The notion of generalized criterion is used to construct a valued outranking relation. All the parameters to be defined have an economic signification, so that the decision maker can easily fix them. Two ways of treatment are proposed: It is possible to obtain either a partial preorder ( Promethee I) or a complete one ( Promethee II), both on a finite set of feasible actions. A comparison is made with the Electre III method. The stability of the results given by the two methods is analysed. Numerical applications are given in order to illustrate the properties of the new methods and some further problems are discussed.

1,887 citations