scholarly journals GPS: Improvement in the Formulation of the TSP for Its Generalizations Type QUBO

2021 ◽  
Author(s):  
Saúl Gonzalez-Bermejo ◽  
Guillermo Alonso-Linaje ◽  
Parfait Atchade-Adelomou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Travelling Salesman Problem ◽  
Quantum Annealing ◽  
Travelling Salesman ◽  
Routing Problem ◽  
Minimum Number ◽  
Binary Formulation ◽  
D Wave

We propose a new binary formulation of the Travelling Salesman Problem (TSP), with which we overcame the best formulation of the Vehicle Routing Problem (VRP) in terms of the minimum number of necessary variables. Furthermore, we present a detailed study of the constraints used and compare our model (GPS) with other frequent formulations (MTZ and native formulation). Finally, we have carried out a coherence and efficiency check of the proposed formulation by running it on a quantum annealing computer, D-Wave\_2000Q6.

scholarly journals FINDING A SOLUTION FOR A COMPLEX STREET ROUTING PROBLEM USING THE MIXED TRANSPORTATION MODE

Transport ◽  
2010 ◽  
Vol 25 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Peter Matis
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Real Data ◽  
Travelling Salesman ◽  
Transportation Mode ◽  
Routing Problem ◽  
Number Of Customers ◽  
The City ◽  
Special Case

The Street Routing Problem (SRP) is a special case of the well-known Vehicle Routing Problem (VRP). The goal is to service a large number of customers in the city zone. New heuristics for solving a complex SRP is evaluated based on real data. This paper presents several approximations to the length of SRP using the mixed transportation mode and compares them with the published approximations used for VRP or Travelling Salesman Problems (TSP). The system was tested in five real world instances ranging from 12 000 to 29 000 customers.

scholarly journals Quantum Annealing of Vehicle Routing Problem with Time, State and Capacity

2019 ◽  
pp. 145-156 ◽  
Author(s):  
Hirotaka Irie ◽  
Goragot Wongpaisarnsin ◽  
Masayoshi Terabe ◽  
Akira Miki ◽  
Shinichirou Taguchi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Quantum Annealing ◽  
Routing Problem

scholarly journals A construction heuristic for finding initial solution to a very large-scale capacitated vehicle routing problem

2021 ◽  
Author(s):  
Bapi Raju Vangipurapu ◽  
Rambabu Govada
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Initial Solution ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Memory Problems ◽  
Sweep Algorithm ◽  
Minimum Number ◽  
Capacitated Vehicle

In this paper, a deterministic heuristic method is developed for obtaining an initial solution to an extremely large-scale capacitated vehicle routing problem (CVRP) having thousands of customers. The heuristic has three main objectives. First, it should be able to withstand the computational and memory problems normally associated with extremely large-scale CVRP. Secondly, the outputs should be reasonably accurate and should have a minimum number of vehicles. Finally, it should be able to produce the results within a short duration of time. The new method, based on the sweep algorithm, minimizes the number of vehicles by loading the vehicles nearly to their full capacity by skipping some of the customers as and when necessary. To minimize the total traveled distance, before the sweeping starts the customers are ordered based on both the polar angle and the distance of the customer from the depot. This method is tested on 10 sets of standard benchmark instances found in the literature. The results are compared with the results of the CW 100 method by Arnold et al. (2019a). The results indicate that the new modified sweep algorithm produces an initial solution with a minimum number of vehicles and with reasonable accuracy. The deviation of the output from the best-known solution (BKS) is within a reasonable limit for all the test instances. When compared with the CW 100 the modified sweep provides a better initial solution than CW 100 whenever the capacity of the vehicle is more and the depot is located eccentrically. The heuristic does not face any memory problems normally associated with the solving of an extremely large-scale CVRP.

scholarly journals Routes Transportation Problem for Waste Collection System at Sitiawan, Perak, Malaysia

2019 ◽  
Vol 9 (2) ◽  
pp. 4605-4609
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Environmental Sustainability ◽  
Vehicle Routing Problem ◽  
Travelling Salesman Problem ◽  
Optimization Method ◽  
Waste Collection ◽  
Collection System ◽  
Routing Problem ◽  
Matlab Programming

Green logistic concept has emerged and inherently driven by the environmental sustainability challenges. The implementation of Vehicle Routing Problem (VRP) in real world relates with Green Vehicle Routing Problem (GVRP). The research is discussing about solving GVRP for waste collection system in Sitiawan, Perak. The purpose of this research is to design a vehicle routes selection for waste collection system using general optimization method and to examine the result associates with GVRP. Travelling Salesman Problem (TSP) is used as main optimization method and simulated using MATLAB Programming. The expected outcome shown in this paper would be statistical analysis between actual routes and suggested routes to find the best routes. Result shows that routes suggested by TSP had better efficiency about 0.32% which had less distance and 7% (392 minutes) less time than actual routes. However, the actual routes had only had slight differences with the suggested TSP routes. Therefore, the result illustrates that the application of actual route selection by the driver is efficient and the suggested routes by TSP can be applied in real world applications.

scholarly journals New Hybrid Quantum Annealing Algorithms for Solving Vehicle Routing Problem

2020 ◽  
pp. 546-561
Author(s):  
Michał Borowski ◽  
Paweł Gora ◽  
Katarzyna Karnas ◽  
Mateusz Błajda ◽  
Krystian Król ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Quantum Annealing ◽  
Routing Problem ◽  
Annealing Algorithms
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