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
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;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900653