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Travelling salesman problem (TSP) is a well known combinatorial optimization problem which has drawn colossal attention due to its eclectic range of applications. In this article, we have proposed two modified versions of intelligent water drops (IWD) algorithm. The first one is the enhanced IWD (e-IWD) algorithm to solve single objective TSP. In the second modification, e-IWD algorithm has been extended to enhanced multi-objective IWD(e-MIWD) algorithm for solving multi-objective TSP. In order to achieve a better exploration capability in both of the proposed algorithms, the soil and velocity parameters of a randomly selected water drop are updated after every iteration of the algorithm when it traverses all the intermediate vertices for a tour. The proposed algorithms have been compared with some other existing similar algorithms on different benchmark instances of TSPs. Furthermore, we have addressed the TSP for both single and multiple objectives under uncertain environment.

There were examined the problems of passage of the regulated parts of a road. There were investigated the changes of a traffic movement intensity in Lutsk (Ukraine) during the spread of Covid-19 pandemic. The graphic dependences of the drivers’ actions estimation while passing the traffic lights objects on a chosen movement route at the beginning of quarantine measures, during the least movement intensity and at the increasing of movement intensity, were obtained. A method of increasing of a possibility of the traffic lights objects nonstop passage was offered.

The Indian Railways Reservation System (IRRS) is one of the world's busiest reservation systems of railway tickets. Recently, the COVID-19 pandemic situation has severely impacted the Indian Railway's (IR) transportation, which eventually has enforced the IR to alter the passenger reservation system. This research attempts to evaluate and analyse the factors that modify the IRRS. In this research, a rough set-based Data Mining Scaffolding (DMS) has been proposed. Here, the relevant preferential information related to the IRRS is managed by introducing a multi-criteria decision-making (MCDM), where a decision-maker (DM) can make a decision based on several decision rules. The effectiveness of the proposed DMS is explained by gathering realistic data of 26 trains, which run between railway stations of two metro cities of India during the COVID-19 pandemic period., Author(s): Haresh Kumar Sharma [1]; Saibal Majumder [2]; Arindam Biswas [3]; Olegas Prentkovskis (corresponding author) [4]; Samarjit Kar [5]; Paulius Skačkauskas [4] 1. Introduction Since the inception of the Rough [...]

This study proposes a hybrid multiple criteria decision making (MCDM) methodology for evaluating the performance of the Indian railway stations (IRS). Since the customers are heterogeneous and their requirements are often imprecise, the evaluation process is a critical step for prioritizing the IRS. To improve the existing approaches, an efficient evaluation technique has been proposed by integrating rough numbers, analytic hierarchy process (AHP) and multi-attribute border approximation area comparison (MABAC) methods in rough environment. The relative criteria weights based on their preferences given by experts is determined by rough AHP whereas evaluation of the alternatives based on these criteria are done by the modified rough MABAC method. A case study of prioritizing different railway stations in India is provided to demonstrate the efficiency and applicability of the proposed method. Among different criteria “proactively” is observed to be the most important criteria in our analysis, followed by ‘Railfanning’ and ‘DMO’ is found to be the best among the forty IRS in this study. Finally, a comparative analysis and validity testing of the proposed method are elaborated and the methodology provides a standard to select IRS on the basis of different criteria.

Dynamically changing economic conditions influence the growing demand of various freights transportation. Inevitably, the demand for heavy and oversized freight transportation is increasing, which is quite problematic. In many cases, it is very difficult to standardize the technology of heavy and oversized freight transportation. Decisions are necessary, which would allow to deliver heavy or oversized freight to the destination place, allocating fewer funds as possible for infrastructure improvements, choosing the most appropriate mode of transport for such freight transportation or using advantages of multimodal (combined) transport. In this article there will be selected methodology of heavy and oversized freight transportation system, carrying heavy and oversized freight by road transport. There will also be made an approval of this methodology, based on a hypothetical route within Lithuanian territory.

During the TDT of 41Cr4 steel specimens, a uniformly reinforced white layer with a nano-crystalline structure is formed in the surface layers. The wear resistance of sliding friction without the lubrication of a pair of steel 41Cr4—grey cast iron EN-GJL-200 (EN) under the face-to-face ("ring-ring") scheme has been studied. It is revealed that when the sliding velocity changes from 0.25 m/s to 4 m/s and the unit load changes from 0.2 MPa to 1.0 MPa, a pair with a reinforced surface layer on 41Cr4 steel specimens and unreinforced specimens of EN-GJL-200 (EN) grey cast iron has a higher wear resistance than an unreinforced pair. The wear resistance increases for both reinforced and not reinforced specimens operating in a friction pair. [ABSTRACT FROM AUTHOR]

The main regularities in fatigue fracture of the railway axle material - the OSL steel - are found in this paper. Micromechanisms of fatigue crack propagation are described and systematized, and a physical-mechanical interpretation of the relief morphology at different stages of crack propagation is proposed for fatigue cracks in specimens cut out of the surface, internal and central layers of the axle.