Paper Info
Title
Simulation results for a daily activity chain optimization method
Abstract
A growing trend, especially in urban environments, is observable towards flexibility in times and locations of activities performed during the day by passengers. In order to optimize the organization of daily activity chains a novel method was elaborated, which introduces flexible demand points. The main idea is that some activities are not necessarily fixed temporally and spatially, therefore they can be realized in different times or locations. Using flexible demand points the method finds all possible combinations and chooses the optimal set of activities by implementing TSP-TW algorithm. The optimum criterion was set as the minimum travel time. The algorithm takes into consideration many constraints, as opening times of the shops or maximum waiting times before the planned arrival. The application of the method results in shorter activity chains and a decrease of travel time for passengers, which has also economical and sociological benefits in long term.
Year
DOI
Venue
2015
10.1109/MTITS.2015.7223265
2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Keywords
Field
DocType
activity planning,traveling salesman problem,flexible points,optimization method,simulation
Observable,Computer science,Simulation,Operations research,Schedule,Artificial intelligence,Travel time,Machine learning
Conference
ISBN
Citations 
PageRank 
978-9-6331-3140-4
0
0.34
References 
Authors
8
2
Name
Order
Citations
PageRank
Domokos Esztergár-Kiss100.34
Zoltan Rozsa291.71