Comparative analysis of selected path-planning approaches in large-scale multi-agent-based environments

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F18%3A50014630" target="_blank" >RIV/62690094:18450/18:50014630 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0957417418304160" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0957417418304160</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2018.07.001" target="_blank" >10.1016/j.eswa.2018.07.001</a>

Result language

angličtina

Original language name

Comparative analysis of selected path-planning approaches in large-scale multi-agent-based environments

Original language description

Large-scale models are currently used for the simulation, analysis and control of real systems, whether technical, biological, social or economic. In multi-agent simulations of virtual economies, it is important to schedule a large number of agents across the cities involved, in order to establish a functional supply chain network for industrial production. This study describes an experimental evaluation of path planning approaches in the field of multi-agent modelling and simulation, applied to a large-scale setting. The experimental comparison is based on a model in which agents represent economic entities and can participate in mutual interactions. For the purposes of experiment, the model is scaled to various degrees of complexity in terms of the numbers of agents and transportation nodes. Various numbers of agents are used to explore the way in which the model&apos;s complexity influences the runtime of the path-planning task. The results indicate that there are significant differences between the runtime performances associated with single approaches, for differing levels of system complexity and model sizes. The study reveals that the appropriate sharing of shortest path information can significantly improve path-planning activities. Hence, this work extends current research in the field of path-planning for multi-agent simulations by conducting an experimental performance analysis of five distinct path-planning approaches and a statistical evaluation of the results. This statistical evaluation contrasts with performance analyses conducted on the basis of &apos;Big O&apos; notation for algorithmic complexity, which describes the limiting behaviour of the algorithm and gives only a rough performance estimate.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Expert systems with applications

ISSN

0957-4174

e-ISSN

—

Volume of the periodical

113

Issue of the periodical within the volume

December

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

415-427

UT code for WoS article

000446288600027

EID of the result in the Scopus database

2-s2.0-85049933474