Abstract
This study focuses on solving the vehicle routing problem (VRP) of E-logistics service providers. In our problem, each vehicle must visit some pick up nodes first, for instance, warehouses to pick up the orders then makes deliveries for customers in the list. Each pickup node has its own list of more than one customers requiring delivery. The objective is to minimize the total travelling cost while real-world application constraints, such as heterogeneous vehicles, capacity limits, time window, driver working duration, etc. are still considered. This research firstly proposes a mathematical model for this multiple pickup and multiple delivery vehicle routing problem with time window and heterogeneous fleets (MPMDVRPTWHF). In the next step, the ant colony optimization algorithm is studied to solve the problem in the large-scale.
Highlights
Chain management, which is the key part of any organization, has a huge impact on the quality of service to customers
The algorithm we propose for the MPMDVRPTWHF has been developed to fit featured constraints in the studied problem including using heterogeneous fleet of vehicles, considering time window, those two constraints can be considered as challenging points for the majority of methods known from the literature
The study adopts the instance set generated by Dominik Goeke (2017) used to solve Pickup and delivery problem with time windows and electric vehicles (PDPTW-EV), besides, it can be used to validate the vehicle routing problem with time window (VRPTW) and Green vehicle routing problem (G-VRP)
Summary
Chain management, which is the key part of any organization, has a huge impact on the quality of service to customers. The problem proposed in this paper can be called a variant of VRPTW which can solve the logistics network pattern that has a set of pickup points that have goods loaded and a set of delivery points that have goods delivered while satisfying the constraint of time-window, a heterogeneous fleet of vehicles and route length limit. Ant colony optimization (ACO) approach is proposed to solve Multiple pickup and multiple delivery vehicle routing problem with time window and heterogeneous fleets. A hybrid approach proposed by [27] combining AS with the savings algorithm to solve the CVRP, improved ACO for the, multiple-depot vehicle routing problem with time windows [28] and there are some other researchers contributing to improve ACO method such as [29] with a new hybrid ant colony optimization algorithm [30,31]. The computational result and conclusions are presented in the final section
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