A personalized urban multicriteria shortest path stochastic optimization algorithm
type: Item
instance of: scholarly article
title: A personalized urban multicriteria shortest path stochastic optimization algorithm
zbMATH Open document ID: 1394.90444
DOI: 10.1155/2015/987358
author: Gong Bowen
author: Lin Ciyun
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: Drivers' route choice behavior is usually personalized and multicriteria in practice. Therefore, the urban shortest path problem is the personalized urban multicriteria shortest path (PUMSP) problem. However, the solutions of the PUMSP problem are difficult to meet the drivers' travel habits in the state of the art. To solve this problem, first, a new stochastic optimization algorithm based on the iterative calculation of a valid route set is proposed in this paper. The effective and reasonable path searching mechanism is designed based on drivers' route choice habits. Then, the evaluation method of calculation results is given. The comparative experimental results with the genetic algorithm show that the proposed algorithm has reached better results in the evaluation parameters and computing time. The experimental results also demonstrate that it is meaningful to consider drivers' travel law in the personalized urban multicriteria shortest path algorithm design for avoiding obtaining impractical routes solutions.
Mathematics Subject Classification ID: 90C15
Mathematics Subject Classification ID: 90C29
zbMATH DE Number: 6927769
Wikidata QID: Q59120146
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/987358
OpenAlex ID: W2179763912
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description: scientific article; zbMATH DE number 6927769