Abstract
Solving the vehicle routing problem (VRP) is one of the best-known optimization issues in the TLS (transport, logistic, spedition) branch market. Various variants of the VRP problem have been presented and discussed in the literature for many years. In most cases, batch versions of the problem are considered, wherein the complete data, including customers’ geographical distribution, is well known. In real-life situations, the data change dynamically, which influences the decisions made by optimization systems. The article focuses on the aspect of geopositioning updates and their impact on the effectiveness of optimization algorithms. Such updates affect the distance matrix, one of the critical datasets used to optimize the VRP problem. A demonstration version of the optimization system was developed, wherein updates are carried out in integration with both open source routing machine and GPS tracking services. In the case of a dynamically changing list of destinations, continuous and effective updates are required. Firstly, temporary values of the distance matrix based on the correction of the quasi-Euclidean distance were generated. Next, the impact of update progress on the proposed optimization algorithms was investigated. The simulation results were compared with the results obtained “manually” by experienced planners. It was found that the upload level of the distance matrix influences the optimization effectiveness in a non-deterministic way. It was concluded that updating data should start from the smallest values in the distance matrix.
Highlights
IntroductionOne of the basic requirements signaled by the TLS (transport, logistic, spedition) market is developing an IT solution enabling effective, quasi-optimal, and quick planning of deliveries to given recipients (destination points)
One of the basic requirements signaled by the TLS market is developing an IT solution enabling effective, quasi-optimal, and quick planning of deliveries to given recipients
The basis for creating the DistMx matrix is a list of destinations (DestPos), containing at least the destination identifier (DestId) and geographical coordinates
Summary
One of the basic requirements signaled by the TLS (transport, logistic, spedition) market is developing an IT solution enabling effective, quasi-optimal, and quick planning of deliveries to given recipients (destination points). Distribution of goods among customers can be classified as the vehicle routing problem (VRP), one of the best-known combinatorial, NP-hard problems [1,2]. It is worth noting, in the case of fleet management, the issue can be classified as a part of WorkForce Management (WFM) [3,4]. The VRP issues need to find an optimal set of routes for a fleet of vehicles to deliver goods to a given group of customers. Improving management efficiency by implementing automated WFM problem optimization systems is still a key market challenge
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
