535 research outputs found
A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives
This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestríaMagister en Ingeniería Industria
Pollution routing problem with time window and split delivery
In most classic vehicle routing problems, the main goal is to minimise the total travel time or distance while, the green vehicle routing problem, in addition to the stated objectives, also focuses on minimising fuel costs and greenhouse gas emissions, including carbon dioxide emissions. In this research, a new approach in Pollution Routing Problem (PRP) is proposed to minimise the CO2 emission by investigating vehicle weight fill level in length of each route. The PRP with a homogeneous fleet of vehicles, time windows, considering the possibility of split delivery and constraint of minimum shipment weight that must be on the vehicle in each route is investigated simultaneously. The mathematical model is developed and implemented using a simulated annealing algorithm which is programmed in MATLAB software. The generated results from all experiments demonstrated that the application of the proposed mathematical model led to the reduction in CO2 emission
Efficient routing of snow removal vehicles
This research addresses the problem of finding a minimum cost set of routes for vehicles in a road network subject to some constraints. Extensions, such as multiple service requirements, and mixed networks have been considered. Variations of this problem exist in many practical applications such as snow removal, refuse collection, mail delivery, etc. An exact algorithm was developed using integer programming to solve small size problems. Since the problem is NP-hard, a heuristic algorithm needs to be developed. An algorithm was developed based on the Greedy Randomized Adaptive Search Procedure (GRASP) heuristic, in which each replication consists of applying a construction heuristic to find feasible and good quality solutions, followed by a local search heuristic. A simulated annealing heuristic was developed to improve the solutions obtained from the construction heuristic. The best overall solution was selected from the results of several replications. The heuristic was tested on four sets of problem instances (total of 115 instances) obtained from the literature. The simulated annealing heuristic was able to achieve average improvements of up to 26.36% over the construction results on these problem instances. The results obtained with the developed heuristic were compared to the results obtained with recent heuristics developed by other authors. The developed heuristic improved the best-known solution found by other authors on 18 of the 115 instances and matched the results on 89 of those instances. It worked specially better with larger problems. The average deviations to known lower bounds for all four datasets were found to range between 0.21 and 2.61%
Thirty years of heterogeneous vehicle routing
It has been around thirty years since the heterogeneous vehicle routing problem was introduced, and significant progress has since been made on this problem and its variants. The aim of this survey paper is to classify and review the literature on heterogeneous vehicle routing problems. The paper also presents a comparative analysis of the metaheuristic algorithms that have been proposed for these problems
A Solution Proposal to Vehicle Routing Problem with Integer Linear Programming: A Distributor Company Sample
It was aimed to minimize the total distance of the routes under the capacity constraint of the routes that a distributor company has drawn in the direction of the demands. To this end, a route to Gebze-based steel production and distribution was drawn up to meet all the demands of a fabrication plant. In order to determine the minimum total distance routes, the solution recommendation by adapting the Capacity Constrained Vehicle Routing Problem (CVRP) which is one of the basic route problems using Branch and Cut algorithm of 0-1 Integer Linear Programming (ILP) was introduced. Distances between the nodes that make up the route are measured via Google Maps. Optimal solutions were obtained by using LINDO computer software to solve the problem.
Performance Comparison of Two-phase LP-based Heuristic Methods for Capacitated Vehicle Routing Problem with Three Objectives
This paper develops a two-phase LP-based heuristic for the Capacitated Vehicle Routing Problem (CVRP). It considers three objectives: (1) minimizing the total costs of fuel consumption and overtime, (2) maximizing the total personal relationships between customers and drivers, and (3) balancing the delivery weights of vehicles. The two-phase LP-based heuristic (cluster-first route-second) is proposed. First, in the clustering stage, three LP-based clustering models (denoted by C1, C2, and C3) are developed. Customers are grouped into clusters based on real distances between the customers for C1, personal relationships between the customers and drivers for C2, and the delivery weights of vehicles for C3. Second, in the routing stage, an LP-based traveling salesman problem model is used to form a route for each cluster, to minimize the total costs of fuel consumption and overtime labor. The experimental results from a case study of Thai SMEs show that when the C2 clustering model is applied, the performances are the best. Significant contributions of this paper include: (1) it is an original paper that proposes the C2 clustering model, and it has the best performances based on the experimental results, and (2) the proposed two-phase LP-based heuristic methods are suitable for practical use by SMEs since the required computational time is short, and it has multiple models with different objectives that can be selected to match a user's requirements
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
- …