A CPU-GPU Parallel Ant Colony Optimization Solver for the Vehicle Routing Problem

被引：7
|
作者：
Rey, Anton [1 ]
Prieto, Manuel [1 ]
Gomez, J., I [1 ]
Tenllado, Christian [1 ]
Ignacio Hidalgo, J. [1 ]
机构：
[1] Univ Complutense Madrid, Fac Informat, Dept Arquitectura Comp & Automat, Prof JG Santesmases 9, E-28040 Madrid, Spain
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2018 | 2018年 / 10784卷
关键词：
ACO; VRP; Parallel; Metaheuristic; GPU; ALGORITHM;
D O I：
10.1007/978-3-319-77538-8_44
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper exposes a new hybrid approach based on Ant Colony Optimization heuristics, Route First-Cluster Second methods and Local search procedures, combined to generate high quality solutions for the Vehicle Routing Problem. This method uses the parallel computing power of modern general purpose GPUs and multicore CPUs, outperforming current ACO-based VRP solvers and showing to be a competitive approach compared to other high performing metaheuristic solvers.
引用
收藏
页码：653 / 667
页数：15
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