17 research outputs found
A novel Dynamic programming approach for Two-Echelon Capacitated Vehicle Routing Problem in City Logistics with Environmental considerations
Abstract The paper proposes a Two-Echelon Capacitated Vehicle Routing Problem with Environmental consideration, intended for managing urban freight distribution in City Logistics. It presents a novel Dynamic programming approach that divides the main problem into several ones and uses an exact algorithm to obtain optimal route paths. The approach applies Fuzzy C-Means Clustering for assigning a group of customers to a satellite. The initial solution is improved with roulette selection, 2-opt, and Or-opt exchange heuristics. The approach was tested on benchmark instances, and obtained results are satisfactory. Moreover, the proposed method highlights the environmental improvement we can obtain in managing urban freight transportation
A Column Generation Based Heuristic for the Multicommodity-ring Vehicle Routing Problem
AbstractWe study a new routing problem arising in City Logistics. Given a ring connecting a set of urban distribution centers (UDCs) in the outskirts of a city, the problem consists in delivering goods from virtual gates located outside the city to the customers inside of it. Goods are transported from a gate to a UDC, then either go to another UDC before being delivered to customers or are directly shipped from the first UDC. The reverse process occurs for pick-up. Routes are performed by electric vans and may be open. The objective is to find a set of routes that visit each customer and to determine ring and gates-UDC flows so that the total transportation and routing cost is minimized. We solve this problem using a column generation-based heuristic, which is tested over a set of benchmark instances issued from a more strategic location-routing problem
Multi-echelon distribution systems in city logistics
In the last decades
,
the increasing quality of services requested by the cust
omer, yields to the necessity of
optimizing
the whole distribution process.
This goal may be achieved through a smart exploitation of
existing resources other than a clever planning of the whole distribution process. For doing that, it is
necessary to enha
nce goods consolidation.
One of the most efficient way to implement
it
is to adopt
Multi
-
Echelon distribution systems
which are very common in
City Logistic context,
in which they allow
to keep large trucks from the city center, with strong
environmental
a
dvantages
.
The aim of the
paper
is to
review
routing
problems
arising
in City Logistics
, in which multi
-
e
chelon distribution systems are
involved: the
Two Echelon
Location Routing Problem (
2E
-
LRP)
, the Two
Echelon Vehicle Routing
Problem (2E
-
VRP) and Truck and Trailer Routing Problem (TTRP), and to discuss literature on
optimization methods, both exact and heuristic, developed to address these problems
A large neighbourhood based heuristic for two-echelon routing problems
In this paper, we address two optimisation problems arising in the context of
city logistics and two-level transportation systems. The two-echelon vehicle
routing problem and the two-echelon location routing problem seek to produce
vehicle itineraries to deliver goods to customers, with transits through
intermediate facilities. To efficiently solve these problems, we propose a
hybrid metaheuristic which combines enumerative local searches with
destroy-and-repair principles, as well as some tailored operators to optimise
the selections of intermediate facilities. We conduct extensive computational
experiments to investigate the contribution of these operators to the search
performance, and measure the performance of the method on both problem classes.
The proposed algorithm finds the current best known solutions, or better ones,
for 95% of the two-echelon vehicle routing problem benchmark instances.
Overall, for both problems, it achieves high-quality solutions within short
computing times. Finally, for future reference, we resolve inconsistencies
between different versions of benchmark instances, document their differences,
and provide them all online in a unified format
Two-Echelon Vehicle and UAV Routing for Post-Disaster Humanitarian Operations with Uncertain Demand
Humanitarian logistics service providers have two major responsibilities
immediately after a disaster: locating trapped people and routing aid to them.
These difficult operations are further hindered by failures in the
transportation and telecommunications networks, which are often rendered
unusable by the disaster at hand. In this work, we propose two-echelon vehicle
routing frameworks for performing these operations using aerial uncrewed
autonomous vehicles (UAVs or drones) to address the issues associated with
these failures. In our proposed frameworks, we assume that ground vehicles
cannot reach the trapped population directly, but they can only transport
drones from a depot to some intermediate locations. The drones launched from
these locations serve to both identify demands for medical and other aids
(e.g., epi-pens, medical supplies, dry food, water) and make deliveries to
satisfy them. Specifically, we present two decision frameworks, in which the
resulting optimization problem is formulated as a two-echelon vehicle routing
problem. The first framework addresses the problem in two stages: providing
telecommunications capabilities in the first stage and satisfying the resulting
demands in the second. To that end, two types of drones are considered. Hotspot
drones have the capability of providing cell phone and internet reception, and
hence are used to capture demands. Delivery drones are subsequently employed to
satisfy the observed demand. The second framework, on the other hand, addresses
the problem as a stochastic emergency aid delivery problem, which uses a
two-stage robust optimization model to handle demand uncertainty. To solve the
resulting models, we propose efficient and novel solution approaches