학술논문

A Two-Phase Distributed Ruin-and-Recreate Genetic Algorithm for Solving the Vehicle Routing Problem With Time Windows
Document Type
Periodical
Source
IEEE Access Access, IEEE. 8:169851-169871 2020
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Genetic algorithms
Optimization
Microsoft Windows
Evolutionary computation
Genetics
Loading
Space exploration
Combinatorial optimization
genetic algorithm
objective function
ruin-and-recreate
vehicle routing problem with time windows
Language
ISSN
2169-3536
Abstract
Developing an algorithm that can solve the vehicle routing problem with time windows (VRPTW) and create near-optimal solutions with the least difference in magnitude is a challenging task. This task is evident from the fact that when an algorithm runs multiple times based on a given instance, the generated solutions deviate from each other and may not near-optimal. For this reason, an algorithm that can solve these problems is effective and highly sought after. This article proposes a novel systematic framework using a two-phase distributed ruin-and-recreate genetic algorithm (RRGA). The two-phase consists of the RRGA phase and ruin-and-recreate (RR) phase, which is designed to run in the distributed computing environment that leveraging these networked resources. This combination of algorithms harnesses the strength of the search diversification and intensification, thereby producing very high-quality solutions. Experiments with Solomon’s benchmark show the RRGA can produce results superior to the recently published hybrid algorithms, best-known solutions, and nine leading hybrid algorithms.