Excursion Groups Flow Forecasting Based on Modified Random Forest
MAGAZINE №4 (99) August 2020
AUTHORS ASLAKHANOV A.R., PAVLOVA E.V.
CATEGORY Information technologies in logistics and SCM Logistics service management Optimization and mathematical modelling Simulation modelling
ABSTRACT
In recent years, both in Russia and worldwide, there has been an annual increase in the number of museum visitors with the most popular exhibitions being visited by millions of people. In 2020, in the context of quarantine measures caused by the COVID-19 pandemic, the issue of managing museum visitors flows has become especially acute. If earlier museums throughput was limited by the maximum duration of possible evacuation from a museum building, exhibition space and the number of employees working with the visitors, in 2020, due to the observance of sanitary and epidemiological rules, the throughput of museums was further reduced. This determines the relevance of analytical solutions for museums as in order to manage visitor flows and adapt services to the high demand, it is necessary to have an effective forecasting model that takes into account the determinism of demand by a number of factors. The purpose of this paper is to develop a forecasting model for the number of excursion groups in specification museum-day-hour. A modification of random forest with the inclusion of more than 450 independent variables in the model is proposed as a forecasting method. The modification of the model relies on changing the mechanism for combining forecasts of trees in the forest in such a way that the weight of the tree in the model is inversely proportional to the measurement error of this tree. The proposed model is tested on the basis of data on more than 20,000 excursion groups of the State Russian Museum for the period 2018-2020. The proposed model showed high accuracy (36.6% WAPE and 0.5% BIAS).
Keywords: forecasting machine learning random forest combining forecasts Python forecast museum Service service quality
Analysis of Trends in the Study of «Green» Logistics
MAGAZINE №2(85) April 2018
AUTHORS Berezhnaya L.Y. - Senior Lecturer, Department of Management, Orenburg State University (Orenburg, Russia)
CATEGORY Analytics and reviews Green Logistics& Supply Chain
ABSTRACT
The increasing role of environment-oriented management methods is reflected in the development of theoretical aspects of "green" logistics. The author of the article analyzed the total number of articles published over the past 8 years on this topic. As a database, three modern science-metric systems have been chosen: Elibrary, SpringerLink, Scopus. Comparative analysis has shown that the number of publications devoted to a certain degree to "green" logistics has grown over the analyzed period of time. Most actively this direction is developing in Russia. However, there is a certain lag in the publication activity in comparison with foreign science-metric databases. The main reasons for some delay in the Russian scientific school have been identified. Within the framework of the article basing on the previous period study the forecasted number of published articles in 2018 is proposed.
Keywords:
Demand planning in supply chains
MAGAZINE №1 (72) February 2016
AUTHOR SOLODOVNIKOV V.V.
CATEGORY Planning the supply chain
ABSTRACT
The paper analyses the demand planning process from supply chain management perspective. The place of the analyzed process in SCOR and GSCF models is investigated. Main steps of the process are clarified: analysis and preparation of historical data; statistical forecasting; manual expert correction of the forecast; forecast verification and confirmation; quality monitoring of forecast and process. Approaches to process data organization are investigated; terminology in this area is presented. The key forecasting methods are analyzed including: qualitative/subjective, cause and effect, time series. Key forecasting models for demand planning in supply chains are systemized. The importance of the quality monitoring of forecasts is highlighted. Main methods of determination of exceptional situations are presented. Key requirements for informational systems of demand planning are formalized. Overview of popular software tools for demand planning is presented.
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Entropy as a measure of the uncertainty of demand in XYZ-model ranking and grouping of resources
MAGAZINE №1 (60) February 2014
AUTHOR ZAYTSEV E.I.
CATEGORY Optimization and economic-mathematical modeling Uncertainty and risk in the supply chain Inventory management
ABSTRACT
In paper the algorithm of perfection classical XYZ-analysis of stocks in logistics is considered. Feature of algorithm is ranging the goods is ranging the goods on accuracy of the forecast. Other feature of algorithm is application of an entropy for definition of uncertainty of demand. It is given an example XYZ - the analysis.
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