Improved Quantum-Inspired Evolutionary Algorithm for Large-Size Lane Reservation
Document Type
Article
Publication Date
12-1-2015
Abstract
This paper studies a lane reservation problem for large sport events in big cities. Such events require organizers to deliver certain people and materials from athlete villages to geographically dispersed venues within a given travel duration. A lane reservation strategy is usually adopted in this circumstance to ensure that time-critical transportation tasks can be completed despite heavy urban traffic congestion. However, it causes negative impact on normal traffic. The problem aims to optimally select and reserve some lanes in a transportation network for the exclusive use of the tasks such that the total traffic impact is minimized. To solve the problem, we first develop an improved integer linear program. Then, its properties are analyzed and used to reduce the search space for its optimal solutions. Finally, we develop a fast and effective quantum-inspired evolutionary algorithm for large-size problems. Computational results on instances with up to 500 nodes in the network and 50 tasks show that the proposed algorithm is efficient in yielding high-quality solutions within a relatively short time.
Identifier
84969963519 (Scopus)
Publication Title
IEEE Transactions on Systems Man and Cybernetics Systems
External Full Text Location
https://doi.org/10.1109/TSMC.2015.2417509
e-ISSN
21682232
ISSN
21682216
First Page
1535
Last Page
1548
Issue
12
Volume
45
Grant
CMMI-1162482
Fund Ref
National Science Foundation
Recommended Citation
    Che, Ada; Wu, Peng; Chu, Feng; and Zhou, Mengchu, "Improved Quantum-Inspired Evolutionary Algorithm for Large-Size Lane Reservation" (2015). Faculty Publications.  6664.
    
    
    
        https://digitalcommons.njit.edu/fac_pubs/6664
    
 
				 
					