DocumentCode
239421
Title
Locality-sensitive hashing based multiobjective memetic algorithm for dynamic pickup and delivery problems
Author
Fangxiao Wang ; Yuan Gao ; Zexuan Zhu
Author_Institution
Coll. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China
fYear
2014
fDate
6-11 July 2014
Firstpage
661
Lastpage
666
Abstract
This paper proposes a locality-sensitive hashing based multiobjective memetic algorithm namely LSH-MOMA for solving pickup and delivery problems with dynamic requests (DPDPs for short). Particularly, LSH-MOMA is designed to find the solution route of a DPDP by optimizing objectives namely workload and route length in an evolutionary manner. In each generation of LSH-MOMA, locality-sensitive hashing based rectification and local search are imposed to repair and refine the individual candidate routes. LSH-MOMA is evaluated on three simulated DPDPs of different scales and the experimental results demonstrate the efficiency of the method.
Keywords
genetic algorithms; vehicle routing; DPDP with dynamic requests; LSH-MOMA algorithm; dynamic pickup-and-delivery problems; locality-sensitive hashing based multiobjective memetic algorithm; route length objective; workload objective; Biological cells; Heuristic algorithms; Lattices; Sociology; Statistics; Vehicle dynamics; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6626-4
Type
conf
DOI
10.1109/CEC.2014.6900653
Filename
6900653
Link To Document