Efficient Implementation of a Genetic Algorithm for the Capacitated Vehicle Routing Problem on a High-Performance FPGA

被引：0

作者：

Heer, Maximilian Jakob ^{[1
]}

Quevedo, Jose ^{[1
]}

Abdelatti, Marwan F. ^{[1
]}

Sendag, Resit ^{[1
]}

Sodhi, Manbir ^{[1
]}

机构：

[1] Univ Rhode Isl, Coll Engn, Kingston, RI 02881 USA

来源：

2023 IEEE 31ST ANNUAL INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES, FCCM | 2023年

关键词：

D O I：

10.1109/FCCM57271.2023.00033

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The Capacitated Vehicle Routing Problem (CVRP) is one of the most relevant optimization problems in operations research and logistics nowadays. While current state-of-the-art solutions to this problem implement evolutionary approaches such as Genetic Algorithms (GAs) on GPUs and multi-core CPUs, this work focuses on implementing a GA for CVRP on a high-performance FPGA to achieve an improved calculation efficiency: While maintaining a comparable solution quality and speed, the FPGA consumes only a fraction of the energy required by traditional computing platforms. This is achieved through leveraging algorithmic parallelism by a custom-fitted hardware architecture, combined with customized data representation for efficient processing.

引用

页码：205 / 205

页数：1