A new metaheuristics for solving vehicle routing problem: Partial Comparison Optimization

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

doi:10.1088/1757-899x/598/1/012023

Cited by 2 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…La Ref. [16] propone un nuevo algoritmo metaheurístico para resolver el problema de ruteo de vehículos VRP con el fin de lograr una solución óptima. El algoritmo propuesto es un algoritmo metaheurístico de optimización de comparación parcial (PCO).…”

Section: Do Not Removeunclassified

Comparison Between the Branch and Bound and Evolutionary Algorithms to Solve the Classic Vehicle Routing Problem Known as VRP

Navarro¹

2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

View full text Add to dashboard Cite

The routing model solution is an algorithmic challenge that seeks to optimize delivery routes to minimize the associated costs. Linear programming is a classical method proposed to find the minimum cost routes. Alternatively, heuristic and metaheuristic methodologies have been proposed to solve the routing problem. The objective of this work is to compare both the average time to find a solution and the average total distance traveled obtained by using an evolutionary genetic algorithm and a linear programming model. Five route configurations with ten, twenty, thirty, forty and fifty customers or nodes to visit were studied. Results pointed out that as the number of customers to visit is duplicated from ten to twenty, the average time to find the best solution is approximately ten times bigger when using a linear programming model. Moreover, when the number of customers doubles from twenty to forty, the average time to find the solution arises something about sixty-eight times the previous time. Conversely, the evolutionary genetic algorithm showed that the average time response to find a solution decreased significantly as the number of customers included in the model increased. Regarding the total distance traveled on the route, the linear programming model found a solution 96.26% lower than that found with the evolutionary method for a route with ten customers to visit, and 48.48% lower on a route with 50 clients. Recommendations based on results indicate that is convenient to find a solution through the linear programming model when fifty or less clients are included in the model. On the contrary, for more than fifty clients, it is more convenient to solve the vehicle routing problem by means of evolutionary genetic algorithms that needs significantly less time to find a problem solution and they also find solutions closer and closer than those found by the linear programming model as the numbers of customers increase.

show abstract

Section: Do Not Removeunclassified

Comparison Between the Branch and Bound and Evolutionary Algorithms to Solve the Classic Vehicle Routing Problem Known as VRP

Navarro¹

2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

View full text Add to dashboard Cite

show abstract

“…The results showed the effectiveness of the proposed algorithm in comparison with GA, ant colony optimization and other metaheuristic algorithms. The authors in [31] propose a new metaheuristic method for solving the traveling salesman problempartial comparison optimization (PCO). PCO is a metaheuristic for solving combinatorial problems like TSP.…”

Section: The Holes Drilling Problemmentioning

confidence: 99%

Increasing the Performance of Computer Numerical Control Machine via the Dhouib-Matrix-4 Metaheuristic

Dhouib

Pezer

2023

View full text Add to dashboard Cite

The Computer Numerical Control (CNC) machine represents a turning point in today's production which has high requirements for product accuracy. The CNC machine enables a high flexibility in work and time saving and also reduces the time required for product accuracy control. Moreover, the CNC machine are used for several activities, most often for turning, drilling and milling operations. Usually, the productivity of any CNC machine can be increased thanks to the minimization of the non-productive of tool movement. In this paper, the results of a new metaheuristic named Dhouib-Matrix-4 (DM4) with an application on the NP-hard problem based on the Travelling Salesman Problem are presented. DM4 is used for increasing the performance of the CNC Machine by optimizing a tool path length in the drilling process performed on the CNC milling machine. The proposed algorithm (DM4) achieves a solution closed to the optimum, compared with the results obtained with the Ant Colony Optimization algorithm and the results found with the manual programming in G code by using a control unit for the selected CNC milling machine.

show abstract

A new metaheuristics for solving vehicle routing problem: Partial Comparison Optimization

Cited by 2 publications

References 17 publications

Comparison Between the Branch and Bound and Evolutionary Algorithms to Solve the Classic Vehicle Routing Problem Known as VRP

Comparison Between the Branch and Bound and Evolutionary Algorithms to Solve the Classic Vehicle Routing Problem Known as VRP

Increasing the Performance of Computer Numerical Control Machine via the Dhouib-Matrix-4 Metaheuristic

Contact Info

Product

Resources

About