Open AccessManaging Dynamically Changing Traffic Flows
Author(s) -
Marina Karaeva,
Natalia Napkhonenko,
V Perevozniuk
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.3.19791
Subject(s) - computer science , heuristic , public transport , set (abstract data type) , genetic algorithm , process (computing) , mathematical optimization , tabu search , field (mathematics) , level of service , operations research , relevance (law) , traffic flow (computer networking) , service (business) , transport engineering , mathematics , algorithm , engineering , artificial intelligence , computer network , machine learning , law , pure mathematics , political science , programming language , operating system , economy , economics
The brief analysis of publications in the field of transport development, the organization and management of urban passenger traffic in the conditions of constantly changing passenger traffics is carried out. The efficiency of using logistic methods is proved by optimization of public passenger transport of the megalopolis. The factors influencing regularity of passenger traffics formation and their dynamic spatial distribution taking into account the main communications between passenger formed points and service providers are revealed. For improvement of traffic flows management the relevance of development of new mathematical models and methods considering relationship of cause and effect between the input and output parameters is established. Methods of solving large-size problems in the conditions of difficult criterion function are considered. Advantages and the prospects of meta-heuristic methods application – genetic algorithms – are shown at the solution of the transport tasks characteristic of unstable streams.For solving the objective using a set of genes is proposed which elements represent a chromosome with a certain set of decisions. Restrictions are formulated and operators of casual changes for a work of genetic algorithm are defined. The algorithm allowing to define and range the key input parameters influencing process of providing transport services and to receive parameters for the output correlation analysis is obtained.