scholarly journals Reflective Nested Simulations Supporting Optimizations within Sequential Railway Traffic Simulators

2022 ◽  
Vol 32 (1) ◽  
pp. 1-34
Author(s):  
Roman Diviš ◽  
Antonín Kavička

This article describes and discusses railway-traffic simulators that use reflective nested simulations. Such simulations support optimizations (decision-making) with a focus on the selection of the most suitable solution where selected types of traffic problems are present. This approach allows suspension of the ongoing main simulation at a given moment and, by using supportive nested simulations (working with an appropriate lookahead), assessment of the different acceptable solution variants for the problem encountered—that is, a what-if analysis is carried out. The variant that provides the best predicted operational results (based on a specific criterion) is then selected for continuing the suspended main simulation. The proposed procedures are associated, in particular, with the use of sequential simulators specifically developed for railway traffic simulations. Special attention is paid to parallel computations of replications both of the main simulation and of supportive nested simulations. The concept proposed, applicable to railway traffic modelling, has the following advantages. First, the solution variants for the existing traffic situation are analyzed with respect to the feasibility of direct monitoring and evaluation of the natural traffic indicators or the appropriate (multi-criterial) function. The indicator values compare the results obtained from the variants being tested. Second, the supporting nested simulations, which potentially use additional hierarchic nesting, can also include future occurrences of random effects (such as train delay), thereby enabling us to realistically assess future traffic in stochastic conditions. The guidelines presented (for exploiting nested simulations within application projects with time constraints) are illustrated on a simulation case study focusing on traffic assessment related to the track infrastructure of a passenger railway station. Nested simulations support decisions linked with dynamic assignments of platform tracks to delayed trains. The use of reflective nested simulations is appropriate particularly in situations in which a reasonable number of admissible variants are to be analyzed within decision-making problem solution. This method is applicable especially to the support of medium-term (tactical) and long-term (strategic) planning. Because of rather high computational and time demands, nested simulations are not recommended for solving short-term (operative) planning/control problems.

2021 ◽  
Vol 11 (4) ◽  
pp. 1660 ◽  
Author(s):  
Ivan Marović ◽  
Monika Perić ◽  
Tomaš Hanak

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.


2021 ◽  
Vol 1 ◽  
pp. 1093-1102
Author(s):  
Flore Vallet ◽  
Mostepha Khouadjia ◽  
Ahmed Amrani ◽  
Juliette Pouzet

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.


2021 ◽  
pp. 1-15
Author(s):  
TaiBen Nan ◽  
Haidong Zhang ◽  
Yanping He

The overwhelming majority of existing decision-making methods combined with the Pythagorean fuzzy set (PFS) are based on aggregation operators, and their logical foundation is imperfect. Therefore, we attempt to establish two decision-making methods based on the Pythagorean fuzzy multiple I method. This paper is devoted to the discussion of the full implication multiple I method based on the PFS. We first propose the concepts of Pythagorean t-norm, Pythagorean t-conorm, residual Pythagorean fuzzy implication operator (RPFIO), Pythagorean fuzzy biresiduum, and the degree of similarity between PFSs based on the Pythagorean fuzzy biresiduum. In addition, the full implication multiple I method for Pythagorean fuzzy modus ponens (PFMP) is established, and the reversibility and continuity properties of the full implication multiple I method of PFMP are analyzed. Finally, a practical problem is discussed to demonstrate the effectiveness of the Pythagorean fuzzy full implication multiple I method in a decision-making problem. The advantages of the new method over existing methods are also explained. Overall, the proposed methods are based on logical reasoning, so they can more accurately and completely express decision information.


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