scholarly journals A GPU Implementation of Local Search Operators for Symmetric Travelling Salesman Problem

2013 ◽  
Vol 25 (3) ◽  
pp. 225-234 ◽  
Author(s):  
Juraj Fosin ◽  
Davor Davidović ◽  
Tonči Carić
Keyword(s):  
Local Search ◽  
Graphics Processing Units ◽  
Travelling Salesman Problem ◽  
Iterated Local Search ◽  
Exact Algorithms ◽  
General Purpose ◽  
Travelling Salesman ◽  
Practical Applications ◽  
Search Approach ◽  
Gpu Implementation

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.

scholarly journals An iterated local search for the travelling salesman problem

2021 ◽  
Author(s):  
Pedro B. Castellucci
Keyword(s):  
Local Search ◽  
Travelling Salesman Problem ◽  
Iterated Local Search ◽  
Travelling Salesman

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.

scholarly journals Solution to travelling salesman problem by clusters and a modified multi-restart iterated local search metaheuristic

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
Keyword(s):  
Local Search ◽  
Travelling Salesman Problem ◽  
Iterated Local Search ◽  
Travelling Salesman

scholarly journals Experimental Study of a Hybrid Genetic Algorithm for the Multiple Travelling Salesman Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Maha Ata Al-Furhud ◽  
Zakir Hussain Ahmed
Keyword(s):  
Genetic Algorithm ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Travelling Salesman Problem ◽  
Hybrid Genetic Algorithm ◽  
Travelling Salesman ◽  
Complex Optimization ◽  
Problem Instances ◽  
Search Approach ◽  
Multiple Travelling Salesman Problem

The multiple travelling salesman problem (MTSP), an extension of the well-known travelling salesman problem (TSP), is studied here. In MTSP, starting from a depot, multiple salesmen require to visit all cities so that each city is required to be visited only once by one salesman only. It is NP-hard and is more complex than the usual TSP. So, exact optimal solutions can be obtained for smaller sized problem instances only. For large-sized problem instances, it is essential to apply heuristic algorithms, and amongst them, genetic algorithm is identified to be successfully deal with such complex optimization problems. So, we propose a hybrid genetic algorithm (HGA) that uses sequential constructive crossover, a local search approach along with an immigration technique to find high-quality solution to the MTSP. Then our proposed HGA is compared against some state-of-the-art algorithms by solving some TSPLIB symmetric instances of several sizes with various number of salesmen. Our experimental investigation demonstrates that the HGA is one of the best algorithms.

On Local Search for Bi-objective Knapsack Problems

2013 ◽  
Vol 21 (1) ◽  
pp. 179-196 ◽  
Author(s):  
Arnaud Liefooghe ◽  
Luís Paquete ◽  
José Rui Figueira
Keyword(s):  
Experimental Study ◽  
Local Search ◽  
Search Algorithm ◽  
Exact Algorithms ◽  
Knapsack Problems ◽  
Optimal Solutions ◽  
Local Search Algorithm ◽  
Property A ◽  
Total Profit ◽  
Search Approach

In this article, a local search approach is proposed for three variants of the bi-objective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is conducted. Based on this property, a local search algorithm is proposed and its performance is compared to exact algorithms in terms of runtime and quality metrics. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact algorithms.

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