scholarly journals An iterated local search for the travelling salesman problem

2021 ◽  
Author(s):  
Pedro B. Castellucci

O Problema do Caixeiro Viajante é um problema clássico da Ciência da Computação, com muitas extensões e variações sendo estudadas ao longo de décadas de pesquisas, principalmente para aplicações relacionadas à logística. Aqui, apresentamos um algoritmo Iterated Local Search (ILS) para encontrar soluções para instâncias do problema proposto pela Competição Brasileira de Descoberta de Conhecimento em Bancos de Dados (KDD-BR). O algoritmo ILS é um algoritmo simples que não depende de nenhuma biblioteca de terceiros. Além disso, foi um dos métodos mais eficazes na competição.

2013 ◽  
Vol 25 (3) ◽  
pp. 225-234 ◽  
Author(s):  
Juraj Fosin ◽  
Davor Davidović ◽  
Tonči Carić

The Travelling Salesman Problem (TSP) is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation problems. The TSP problem is NP-hard problem and requires large computation power to be solved by the exact algorithms. In the past few years, fast development of general-purpose Graphics Processing Units (GPUs) has brought huge improvement in decreasing the applications’ execution time. In this paper, we implement 2-opt and 3-opt local search operators for solving the TSP on the GPU using CUDA. The novelty presented in this paper is a new parallel iterated local search approach with 2-opt and 3-opt operators for symmetric TSP, optimized for the execution on GPUs. With our implementation large TSP problems (up to 85,900 cities) can be solved using the GPU. We will show that our GPU implementation can be up to 20x faster without losing quality for all TSPlib problems as well as for our CRO TSP problem.


PLoS ONE ◽  
2018 ◽  
Vol 13 (8) ◽  
pp. e0201868 ◽  
Author(s):  
Gustavo Erick Anaya Fuentes ◽  
Eva Selene Hernández Gress ◽  
Juan Carlos Seck Tuoh Mora ◽  
Joselito Medina Marín

2017 ◽  
Vol 28 (6) ◽  
pp. 807-820 ◽  
Author(s):  
Mariana Guersola ◽  
Maria Teresinha Arns Steiner ◽  
Cassius Tadeu Scarpin

Purpose Liquefied petroleum gas (LPG) transportation risks depend on aspects such as the total length of the trip and population density along the route. Choosing to deliver the product on non-busy days and reducing distances travelled may help to reduce these risks and lower the level of air pollution generated by the transportation trucks. The purpose of this paper is to reduce LPG delivery impact. Design/methodology/approach A three-stage methodology is proposed. First, rules are created in order to choose which clients have to be visited each day to avoid deliveries in downtown areas during business days. Second, an Iterated Local Search (ILS) metaheuristic is proposed for the capacitated p-median problem to group the chosen customers. Finally, another ILS is proposed to solve the Travelling Salesman Problem, for each truck to follow a better route while visiting its customers. Findings The methodology resulted in a 24.8 per cent reduction in distances travelled, representing an annual reduction of 32,716 kg in CO2 emissions. The average amount of product sold per kilometre travelled improved by 72 per cent. Originality/value The literature shows a clear need for companies to consider sustainability in their daily decisions. However, especially in developing countries, there is a fear that protecting the environment may cost money. This main contribution of this paper is that it presents a real solution, serving as a guide for companies to improve their transportation system, resulting in environmental and economic benefits.


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