Multi-GPU parallel memetic algorithm for capacitated vehicle routing problem

TL;DR

This paper introduces a parallel memetic algorithm for the capacitated vehicle routing problem, leveraging GPU computing to improve efficiency, with theoretical analysis and experimental validation for various vehicle capacities.

Contribution

It presents a novel parallel memetic algorithm tailored for the capacitated vehicle routing problem and demonstrates its effectiveness through theoretical and experimental analysis.

Findings

Polynomial-time algorithm for capacity 2

Efficient GPU-based implementation for larger capacities

Experimental results show improved solution quality

Abstract

The goal of this paper is to propose and test a new memetic algorithm for the capacitated vehicle routing problem in parallel computing environment. In this paper we consider simple variation of vehicle routing problem in which the only parameter is the capacity of the vehicle and each client only needs one package. We present simple reduction to prove the existence of polynomial-time algorithm for capacity 2. We analyze the efficiency of the algorithm using hierarchical Parallel Random Access Machine (PRAM) model and run experiments with code written in CUDA (for capacities larger than 2).