Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

Stević, Željko; Pamučar, Dragan; Vasiljević, Marko; Stojić, Gordan; Sanja, Korica

doi:10.3390/sym9110279

Cited by 120 publications

(86 citation statements)

References 111 publications

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“…According to Khoo et al [42], a very important advantage of using rough set theory to handle vagueness and uncertainty is that it expresses vagueness by means of the boundary region of a set instead of membership function. In addition, the integration of rough numbers in MCDM methods gives the possibility to explore subjective and unclear evaluation of the experts and to avoid assumptions, which is not the case when applying fuzzy theory [35]. According to Hashemkhani Zolfani et al [10], the main advantage of the WASPAS method is its high degree of reliability.…”

Section: Applications Of Rough Sets In Multiple Criteria Decision Makmentioning

confidence: 99%

“…The model presented in the paper is solved by using the following methods: rough SAW [39], rough EDAS [35], rough MABAC [32], rough VIKOR [47], rough MAIRCA [43] and rough MULTIMOORA [35]. Their results and comparison with the rough WASPAS approach are shown in Figure 2.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…A rough AHP and rough TOPSIS approach is also used in [34]. Rough numbers in integration with MCDM methods, according Stević et al [35], give good results, so lately we can notice the popularization of the use of rough numbers [36][37][38]. Besides the AHP method and its rough form, it is also possible to apply rough best worst method (BWM).…”

Section: Applications Of Rough Sets In Multiple Criteria Decision Makmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

et al. 2018

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Abstract:The decision-making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as supply chain management. One of the most important items in the initial phase of the supply chain, which strongly influences its further flow, is to decide on the most favorable supplier. In this paper a selection of suppliers in a company producing polyvinyl chloride (PVC) carpentry was made based on the new approach developed in the field of multi-criteria decision making (MCDM). The relative values of the weight coefficients of the criteria are calculated using the rough analytical hierarchical process (AHP) method. The evaluation and ranking of suppliers is carried out using the new rough weighted aggregated sum product assessment (WASPAS) method. In order to determine the stability of the model and the ability to apply the developed rough WASPAS approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ in the first part. The second part of the sensitivity analysis relates to the application of different multi-criteria decision-making methods in combination with rough numbers that have been developed in the very recent past. The model presented in the paper is solved by using the following methods: rough Simple Additive Weighting (SAW), rough Evaluation based on Distancefrom Average Solution (EDAS), rough MultiAttributive Border Approximation area Comparison (MABAC), rough Višekriterijumsko kompromisno rangiranje (VIKOR), rough MultiAttributiveIdeal-Real Comparative Analysis (MAIRCA) and rough Multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA). In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient (SCC) of the ranks obtained was calculated which confirms the applicability of all the proposed approaches. The proposed rough model allows the evaluation of alternatives despite the imprecision and lack of quantitative information in the information-management process.

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Section: Applications Of Rough Sets In Multiple Criteria Decision Makmentioning

confidence: 99%

Section: Sensitivity Analysismentioning

confidence: 99%

Section: Applications Of Rough Sets In Multiple Criteria Decision Makmentioning

confidence: 99%

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A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

et al. 2018

Self Cite

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“…As for parameter estimation from empirical data-sometimes it is even possible to develop the patterns describing judicial decisions; in a recent research a large collection of judicial cases was used to measure the probabilities quite precisely [20]. It is important to note that the sensitivity analysis is out of the scope of this research; for example, probability values can be perturbed in order to gather more general results that are robust to errors of estimation of probability values in a similar way to what was done by other authors [21,22]. Some recent studies propose a comprehensive sensitivity analysis to identify the uncertain parameters that significantly influence the decision-making process in investments, and quantify their degree of influence [23].…”

Section: Introductionmentioning

confidence: 99%

An Algorithm for Modelling the Impact of the Judicial Conflict-Resolution Process on Construction Investment

Bugajev

Šostak

2018

Sustainability

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Abstract:In this article, the modelling of the judicial conflict-resolution process is considered from a construction investor's point of view. Such modelling is important for improving the risk management for construction investors and supporting sustainable city development by supporting the development of rules regulating the construction process. Thus, this raises the problem of evaluation of different decisions and selection of the optimal one followed by distribution extraction. First, the example of such a process is analysed and schematically represented. Then, it is formalised as a graph, which is described in the form of a decision graph with cycles. We use some natural problem properties and provide the algorithm to convert this graph into a tree. Then, we propose the algorithm to evaluate profits for different scenarios with estimation of time, which is done by integration of an average daily costs function. Afterwards, the optimisation problem is solved and the optimal investor strategy is obtained-this allows one to extract the construction project profit distribution, which can be used for further analysis by standard risk (and other important information)-evaluation techniques. The overall algorithm complexity is analysed, the computational experiment is performed and conclusions are formulated.

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“…Thus, we can make the evaluation process with a high degree of flexibility. In addition, the assessments of experts can be made under supplier selection [39], architectural shape of the buildings [40], cultural heritage structures [41], quality assurance [42], evaluation in logistics [43,44] and stairs shape assessment [45].…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Fuzzy Approach Based on the EDAS Method for Multi-Criteria Subcontractor Evaluation

et al. 2018

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Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM) problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution) method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

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Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

Cited by 120 publications

References 111 publications

A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

An Algorithm for Modelling the Impact of the Judicial Conflict-Resolution Process on Construction Investment

A Dynamic Fuzzy Approach Based on the EDAS Method for Multi-Criteria Subcontractor Evaluation

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