scholarly journals SOLVING CONSTRUCTION PROJECT SELECTION PROBLEM BY A NEW UNCERTAIN WEIGHTING AND RANKING BASED ON COMPROMISE SOLUTION WITH LINEAR ASSIGNMENT APPROACH

2019 ◽  
Vol 25 (3) ◽  
pp. 241-251 ◽  
Author(s):  
Reza Davoudabadi ◽  
Seyed Meysam Mousavi ◽  
Jonas Šaparauskas ◽  
Hossein Gitinavard
Keyword(s):  
Fuzzy Sets ◽  
Alternative Assessment ◽  
Construction Project ◽  
Project Selection ◽  
Selection Problem ◽  
Uncertain Information ◽  
Compromise Solution ◽  
Additional Information ◽  
Criteria Weights ◽  
Linear Assignment

Selecting a suitable construction project is a significant issue for contractors to decrease their costs. In real cases, the imprecise and uncertain information lead to decisions made based on vagueness. Fuzzy sets theory could help decision makers (DMs) to address incomplete information. However, this article develops a new integrated multi-criteria group decision-making model based on compromise solution and linear assignment approaches with interval-valued intuitionistic fuzzy sets (IVIFSs). IVIFSs by presenting a membership and non-membership degree for each candidate based on appraisement criteria could decrease the vagueness of selection decisions. The proposed algorithm involves a new decision process under uncertain conditions to determine the importance of criteria and DMs, separately. In this regard, no subjective or additional information is needed for this process; only the input information required is an alternative assessment matric. In this approach, weights of criteria and DMs are specified based on novel indexes to increase the reliability of obtained results. In this respect, the criteria’ weights are computed regarding entropy concepts. The basis for calculating the weight of each DM is the distance between each DM and an average of the DMs’ community. Furthermore, the linear assignment model is extended to rank the candidates. A case study about the construction project selection problem (CPSP) is illustrated to indicate the application of proposed model.

scholarly journals An Integrated Single-Valued Neutrosophic Combined Compromise Solution Methodology for Renewable Energy Resource Selection Problem

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4594
Author(s):  
Pratibha Rani ◽  
Jabir Ali ◽  
Raghunathan Krishankumar ◽  
Arunodaya Raj Mishra ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Selection Process ◽  
Energy Resource ◽  
Strategic Decision ◽  
Selection Problem ◽  
Illustrative Case ◽  
Compromise Solution ◽  
Neutrosophic Sets ◽  
Technical Requirements ◽  
Criteria Weights

Optimal renewable energy source (RES) selection needs a strategic decision for reducing environmental pollutions, use of conventional resources, and improving economic development. In the process of RESs evaluation, several aspects like environmental, economic, social, and technical requirements play an important role. In addition, diverse factors affect the appropriate RES selection problem which adheres to uncertain and imprecise data. Thus, this selection process can be considered as a complex uncertain multi-criteria decision making (MCDM) problem. This study aims to introduce a novel integrated methodology based on Step-wise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) methods within single-valued neutrosophic sets (SVNSs) context, wherein the decision-makers and criteria weights are completely unknown. In the proposed approach, the criteria weights are determined by the SWARA method, and the most suitable RES alternative is determined by an improved CoCoSo method under the SVN context. Further, an illustrative case study of RES selection is considered to demonstrate the thorough execution process of the proposed method. Moreover, a comparison with existing methods is discussed to analyze the validity of the obtained result. This study performs sensitivity analysis with a various set of criteria weights to reveal the robustness of the developed approach. The strength of the proposed method is its practical applicability and ability to provide solutions under uncertain, imperfect, indeterminate, and inconsistent information.

Processing uncertain information in the linear space of fuzzy sets

1991 ◽  
Vol 44 (2) ◽  
pp. 187-198 ◽  
Author(s):  
Wladyslaw Homenda ◽  
Witold Pedrycz
Keyword(s):  
Fuzzy Sets ◽  
Linear Space ◽  
Uncertain Information

scholarly journals A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers

2021 ◽  
Vol 13 (4) ◽  
pp. 2064
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Raghunathan Krishankumar ◽  
Edmundas Kazimieras Zavadskas ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Reverse Logistics ◽  
Hybrid Approach ◽  
Third Party ◽  
Illustrative Case ◽  
Primary Concern ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Criteria Weights ◽  
Reverse Logistic ◽  
Illustrative Case Study

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

scholarly journals A BI-OBJECTIVE SCORE-VARIANCE BASED LINEAR ASSIGNMENT METHOD FOR GROUP DECISION MAKING WITH HESITANT FUZZY LINGUISTIC TERM SETS

2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Assignment Method ◽  
Linguistic Term ◽  
Criteria Weights ◽  
Individual Evaluation ◽  
Fuzzy Linguistic ◽  
Linear Assignment

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

scholarly journals Evidence Theory in Picture Fuzzy Set Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Harish Garg ◽  
R. Sujatha ◽  
D. Nagarajan ◽  
J. Kavikumar ◽  
Jeonghwan Gwak
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Evidence Theory ◽  
Belief Function ◽  
Uncertain Information ◽  
Interval Probability ◽  
Dempster Shafer Theory ◽  
Effective Manner ◽  
Picture Fuzzy Set ◽  
Shafer Theory

Picture fuzzy set is the most widely used tool to handle the uncertainty with the account of three membership degrees, namely, positive, negative, and neutral such that their sum is bound up to 1. It is the generalization of the existing intuitionistic fuzzy and fuzzy sets. This paper studies the interval probability problems of the picture fuzzy sets and their belief structure. The belief function is a vital tool to represent the uncertain information in a more effective manner. On the other hand, the Dempster–Shafer theory (DST) is used to combine the independent sources of evidence with the low conflict. Keeping the advantages of these, in the present paper, we present the concept of the evidence theory for the picture fuzzy set environment using DST. Under this, we define the concept of interval probability distribution and discuss its properties. Finally, an illustrative example related to the decision-making process is employed to illustrate the application of the presented work.

scholarly journals Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yoonseok Shin
Keyword(s):  
Cost Estimation ◽  
Construction Projects ◽  
High Performance ◽  
Learning Algorithm ◽  
Early Stage ◽  
Construction Project ◽  
Regression Tree ◽  
Building Construction ◽  
Regression Problem ◽  
Additional Information

Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.

scholarly journals An Analysis of the Decisive Criteria in Formwork Selection Problem

2016 ◽  
Vol 62 (1) ◽  
pp. 185-196 ◽  
Author(s):  
A. Krawczyńska-Piechna
Keyword(s):  
Selection Problem ◽  
Exact Form ◽  
Factors Affecting ◽  
Work System ◽  
Criteria Weights ◽  
Survey Results

Abstract The present paper concerns a problem of decisive criteria and their order in formwork selection problem. As the factors affecting the choice of exact form work system have been often discussed in literature, their importance has not been distinctly formulated yet, what hampers aiding formwork selection with MCDA methods that require criteria weights (eg.: SAW, TOPSIS etc.). Therefore, author ran a survey - the decisive criteria were recognized and verified within polls send to various contractors. An analysis of survey results including criteria ordering is a subject of the present elaboration.

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