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Proceedings ArticleDOI

A quantitative research for determining the user requirements for an innovative route planning system targeted for the commercial vehicle fleets

TLDR
In this paper, the authors present a quantitative research related to the user requirements for a software platform that deals with Planning, Optimizing and Monitoring Logistics Vehicle Fleets, which will provide insights for future development.
Abstract
The number of online orders placed by customers have increased rapidly in the last years leading to a transportation logistics problem. The order management process is a challenge for most companies which is why investing in new software smart solutions can give an advantage over competitors. In this article we present a quantitative research related to the user requirements for a software platform that deals with Planning, Optimizing and Monitoring Logistics Vehicle Fleets, which will provide insights for future development. The software platform must have functionalities which are trending on the market and take into consideration the current transportation issues. This paper is based on the work on Eureka project PN-III-P3-3.5-EUK2019-0210.

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Proceedings ArticleDOI

Architecture of an Innovative Route Planning System for Sustainable Commercial Vehicle Fleets

TL;DR: The system architecture of iRoute, an innovative route planning solution specialized for commercial vehicle fleets, considering also electrical vehicles with specific constraints about their drive autonomy and charging stations along the optimized route is described.
References
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Journal ArticleDOI

Models for Evaluating and Planning City Logistics Systems

TL;DR: This work focuses on a challenging city logistics planning issue, the integrated short-term scheduling of operations and management of resources, for the general case involving a two-tiered distribution structure.
Journal ArticleDOI

Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints

TL;DR: A review of the recent developments that had a major impact on the current state-of-the-art exact algorithms for the vehicle routing problem (VRP) can be found in this paper.
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Online Vehicle Routing With Neural Combinatorial Optimization and Deep Reinforcement Learning

TL;DR: This paper transforms the online routing problem to a vehicle tour generation problem, and proposes a structural graph embedded pointer network to develop these tours iteratively and shows that the proposed strategy can significantly outperform conventional strategies with limited computation time in both static and dynamic logistic systems.
Journal ArticleDOI

A priori optimization with recourse for the vehicle routing problem with hard time windows and stochastic service times

TL;DR: This paper formulate the VRPTW-ST as a set partitioning problem and solve it by exact branch-cut-and-price algorithms and developed efficient labeling algorithms by suitably choosing label components, determining extension functions, and developing lower and upper bounds on partial route reduced cost to be used in the column generation step.
Journal ArticleDOI

On determining optimal fleet size and vehicle transfer policy for a car rental company

TL;DR: This paper develops a two-stage dynamic programming model, in which the vehicle transfer policy in the second stage and the optimal fleet size in the first stage are determined and proposes a heuristic solution, which is based on a special case analysis, for the fleet size problem.