List of Abstracts 2016: SESSION C - TRANSPORT
Date: November 29, 2016
Forecasting the future volume of traffic at the intersection may lead to increasing the drivers safety on city road. The possibility of forecasting methods realization for the transportation system is an important element of traffic management in the city. In the article the forecast for future periods will be calculated on the basis of cyclical fluctuations in the traffic flow using the method of harmonic analysis. Data to determine the forecast are coming from the intersection of the Słowackiego avenue and Łobzowska street that were registered with an interval of time during one week. Cyclical fluctuations are typical for the period exceeding one year. The article aims to prove the application of harmonic analysis for hourly periods. The forecast is confirmed using relative and the absolute forecast error.
This article presents a proposition of classification of work of the supplies in the time of the delivery process at the last 100 meters in the city center. Based on fieldwork with 900 points is has been shown how the energy expenditure of supplier depends on the technology used to unload and the movement of goods to the customer. This article presents a proposition for creation of the computer software to calculate the energy expenditure of the supplier.
The main objective of this work is to point out all weaknesses in the sorting of the consignments.
The output of the paper is a proposal a suitable alternative for unloading, sorting and transhipment consignments using multi-criteria decision-making. In the decision-making process, the focus is on energy consumption and investment costs in case of using new technical equipment. The proposed solution shorten the sorting time, reduce the risk of parcels damage and increasing the security and continuity of the work in the depot.
Transport management process is supported by different types of tools helping managers to achieve strategic logistics goals. As the logistics goals are supposed to be in line with company’s strategy, the choice of the tool should also be made based on its ability to help company’s development and creation of competitive advantages. Increasingly, the search for competitive advantages takes place in areas of sustainable development. However, transport operations are rarely indicated as those that add value to the company in the area of its sustainable development. That is why it is important to study and develop transport management tools that will be able supporting the increasing use of transport modes that are environmentally friendly. This is also the main objective ChemMultimodal Project – promotion of multimodal transport of chemical goods. The project aims to achieve this by coordinating and facilitating cooperation between chemical companies, specialized logistics service providers (LSP), terminal operators and public authorities in chemical regions in Central Europe. The Project is realized in the Interreg Programme between June 2016 and May 2019. The aim of the article is to present the effects of the first phase of the project – the results of transport management tools used in Polish Chemical Sector study conducted between August and September 2016.
The bus arrival time is one of the key elements in public transport information systems. The amount of Automated Vehicle Location (AVL) systems is growing, therefore in this paper we aim to provide a cloud-based machine learing solution of this problem. Using bus location data we created models in Microsoft Azure Machine Learing Studio using different machine learning methods: Artifical Neural Network (ANN), Support Vector Machine (SVM) and Linear Regression (LR). We validated the methods using historical data and compared the results to naïve predictions that use either historical data with a delay or a vehicle speed.
This paper presents the problem of technological transport means selection to specific mining and geological conditions in open cast surface mining. The problem is formulated as a multiple criteria ranking of variants. They are presented as technological vehicles evaluated by the family of criteria. The set of considered criteria is composed of ten parameters, including the following aspects: economic, technical and construction, exploitation and reliability. The group of decision makers is composed of experts with different expertise profiles, i.e. (a) academic – surface mining, (b) academic – machine operation, (c) industrial - management of surface mining, (d) joint academic and industrial profile.
The solution of this problem is carried out with an application of stochastic group decision aiding method proposed by the authors of this paper. This approach is composed of five steps, i.e.: 1) definition of the decision problem, 2) construction of variants, set of criteria and models of decision makers’ (different experts) preferences, 3) computation of rankings with respect to the stochastic model of preferences, 4) definition of the final ranking, 5) discussion of results.
The obtained results are compared with the previous research (Bodziony P., Kasztelewicz Z. i Sawicki P., 2016) where the selection of transportation means is based on separate deterministic preferences of each expert.
Reference:
Bodziony P., Kasztelewicz Z., Sawicki P., The problem of multiple criteria selection of the surface mining haul trucks. Archives of Mining Sciences, 2016, Vol. 61, No 2, pp. 223-243, doi:
10.1515/amsc-2016-0017.
In this paper we consider the well known Hub and Spoke problem according to the Warsaw Public Transport System. Our approach is based on data available on the website of the ZTM (Urban Transport Company) and an evolutionary algorithm method that detects communication hubs well connected (with the high capacity of available transport means) with the center of the city and other detected hubs. These hubs can become the skeleton of the public transport system and can be good point for localization of Park and Ride car parks for instance.