Spatio-Temporal Effects on Decision Making in Green Fleet Supplier Selection: Insights and Implications for Best Value Procurement Policy Objectives in Public Transportation

2021 ◽  
Author(s):  
Marc Scott
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Supplier Selection ◽  
Temporal Effects ◽  
Procurement Policy ◽  
Best Value ◽  
Policy Objectives ◽  
Spatio Temporal

An Interval Valued Neutrosophic Decision-Making Structure for Sustainable Supplier Selection

2021 ◽  
pp. 115354
Author(s):  
Morteza Yazdani ◽  
Ali Ebadi Torkayesh ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Sahand Asgharieh Ahari ◽  
...  
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Sustainable Supplier Selection ◽  
Interval Valued

scholarly journals DESIGNING A DATA VISUALISATION AND ANALYSIS TOOL FOR SUPPORTING DECISION-MAKING WITH PUBLIC TRANSPORTATION NETWORK

2021 ◽  
Vol 1 ◽  
pp. 1093-1102
Author(s):  
Flore Vallet ◽  
Mostepha Khouadjia ◽  
Ahmed Amrani ◽  
Juliette Pouzet
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Transportation Network ◽  
Visual Exploration ◽  
Problem Solution ◽  
Analysis Tool ◽  
Complex Data ◽  
Data Visualisation ◽  
Ex Post ◽  
Passenger Flows

AbstractMassive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flows, notably in disrupted situations. We propose a problem-solution process combined with data visualisation. It relies on the observation of operational agents, creativity sessions and the development of user scenarios. The process is illustrated for a case study on one of the commuter line of the Paris metropolitan area. Results encompass three different layers and multiple interlinked views to explore spatial patterns, spatio-temporal clusters and passenger flows. We join several transport network indicators whether are measured, forecasted, or estimated. A user scenario is developed to investigate disrupted situations in public transport.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

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