Paper Info
Title
Multi-objective memetic algorithm for solving pickup and delivery problem with dynamic customer requests and traffic information
Abstract
This paper formulates one-to-many-to-one pickup and delivery problems with dynamic customer requests and traffic information. A multi-objective memetic algorithm namely prioLSH-MOMA is proposed to solve the problems. The new algorithm is characterized with a priority and locality-sensitive hashing based local search. prioLSH-MOMA is designed to find an optimal route of a dynamic pickup and delivery problem in terms of route length and workload. Particularly, a re-planning strategy is introduced to handle the dynamic information. Priority and locality-sensitive hashing based local search is applied to fine-tune the candidate routes during the evolution process. prioLSH-MOMA is evaluated with two dynamic pickup and delivery problems simulated on real-world maps and the results demonstrate the efficiency of the proposed algorithm. © 2016 IEEE.
Year
DOI
Venue
2016
10.1109/CEC.2016.7744028
2016 IEEE Congress on Evolutionary Computation, CEC 2016
Keywords
Field
DocType
Memetic Algorithm, Multi-objective Optimization, Dynamic Pickup and Delivery Problem, Locality-Sensitive Hashing
Memetic algorithm,Mathematical optimization,Computer science,Workload,Decision support system,Evolutionary computation,Hash function,Local search (optimization),Pickup,Delivery problems
Conference
Citations 
PageRank 
References 
0
0.34
16
Authors
5
Name
Order
Citations
PageRank
Xiao Jun100.34
Yang Yanming200.34
Xiaoliang Ma318218.51
Jiarui Zhou4705.61
Zexuan Zhu598957.41