scholarly journals Reactive GRASP for the prize-collecting covering tour problem

2021 ◽  
Author(s):  
glaubos climaco ◽  
Isabel Rosseti ◽  
Rogério Da Silva ◽  
Marcos Guerine
Keyword(s):  
Processing Time ◽  
Variable Neighborhood Search ◽  
State Of The Art ◽  
Random Variable ◽  
Neighborhood Search ◽  
Search Procedure ◽  
Adaptive Search ◽  
Hybrid Heuristic ◽  
Prize Collecting ◽  
Covering Tour Problem

This paper presents a greedy randomized adaptive search procedure (GRASP) for the prize-collecting covering tour problem, which is the problem of finding a route for traveling teams that provide services to communities geographically distant from large urban locations. We devised a novel hybrid heuristic by combining a reactive extension of the GRASP with Random Variable Neighborhood Search (VND) meta-heuristic for the purpose of solving the PCCTP. Computational experiments were conducted on a PCCTP benchmark from the literature, and the results demonstrate our approach provides a significant improvement in solving PCCTP and comparable with the state-of-the-art, mainly regarding the computational processing time.

scholarly journals An ILS algorithm with RVND for the green vehicle routing problems with time-varying speeds

2018 ◽  
Author(s):  
Darci José Mendes Júnior ◽  
Luciana Brugiolo Gonçalves ◽  
Stênio Sã R. F. Soares
Keyword(s):  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Random Variable ◽  
Human Action ◽  
Iterated Local Search ◽  
Neighborhood Search ◽  
Time Varying ◽  
Search Procedure ◽  
Local Search Algorithm ◽  
Randomized Search

The environmental impacts of human action have led several countries to create stricter laws and tax breaks to reduce this damage. Thereby, the Green Logistic has been increasingly sought to meet the requirements and needs for a more sustainable development. This work presents an ILS (Iterated Local Search) algorithm combined with RVND (Random Variable Neighborhood Search) and compare it with a GRASP (Greed Randomized Search Procedure) algorithm where each one has two variations: minimize distance and minimize emission. The results show the effectiveness of the ILS approach and heuristics that minimize the total distance covered do not present themselves as good solutions in terms of sustainability.

scholarly journals Profitable Tour Problem with Passengers and Time and Cost Restrictions

2018 ◽  
Author(s):  
Vinícius A. Petch ◽  
Marco Cesar Goldbarg ◽  
Elizabeth F. G. Goldbarg ◽  
José G. L. Filho
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Search Procedure ◽  
Adaptive Search

Este artigo tem como objetivo apresentar um novo problema no contexto do transporte colaborativo denominado Problema do Passeio Lucrativo com Passageiros e Restrições de Tempo e Custo. O problema consiste em determinar a melhor rota de um courier que precisa realizar serviços em diversos locais. O courier realiza seu percurso em um veículo. Para reduzir custos, o courier pode levar passageiros que compartilham com ele os custos de viagem. Um modelo matemático é proposto o qual é implementado em um solver e aplicado a instâncias do problema. São apresentados algoritmos heurísticos segundo as meta-heurísticas Variable Neighborhood Search e Greedy Randomized Adaptive Search Procedure. São relatados resultados de um experimento computacional com 36 instâncias com até 150 vértices.

Alocação de Geradores Distribuídos em Sistemas de Distribuição de Energia Elétrica Utilizando Algoritmo GRASP-VNS

2020 ◽  
Author(s):  
Bruno A. R. Silva ◽  
Wilingthon G. Zvietcovich ◽  
Francisco R. A. C. Baracho ◽  
Laerty J. S. Damião ◽  
Laura F. Souza
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Search Procedure ◽  
Adaptive Search

Este trabalho apresenta a implementação das meta-heuristicas, Greedy Randomized Adaptive Search Procedure (GRASP) e Variable Neighborhood Search (VNS) para a alocação ótima de Geradores Distribuídos (GDs) e seu dimensionamento em redes de distribuição com operação radial, visando a redução das perdas elétricas ativas e, simultaneamente, à melhoria dos níveis de tensão. Nesta metodologia, o algoritmo GRASP é utilizado para a construção de possíveis soluções do problema, enquanto o VNS se aplica à uma etapa de busca local, na qual realiza-se um refinamento no espaço de soluções para aprimorar a convergência do processo de busca. Para validação da técnica, a metodologia foi aplicada em duas redes, uma de 33 barras do IEEE e outra de 135 barras. Dos resultados obtidos, pôde-se verificar a eficácia da metodologia em encontrar soluções de boa qualidade com perdas mínimas e consideráveis melhorias nos perfis de tensão.

scholarly journals Two meta-heuristics for solving the multi-vehicle multi-covering tour problem with a constraint on the number of vertices

2020 ◽  
pp. 14-14
Author(s):  
Manel Kammoun ◽  
Houda Derbel ◽  
Bassem Jarboui
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Descent Method ◽  
Computational Experiments ◽  
Neighborhood Search ◽  
Variable Neighborhood Descent ◽  
Covering Tour Problem ◽  
Neighborhood Search Algorithm

In this work we deal with a generalized variant of the multi-vehicle covering tour problem (m-CTP). The m-CTP consists of minimizing the total routing cost and satisfying the entire demand of all customers, without the restriction of visiting them all, so that each customer not included in any route is covered. In the m-CTP, only a subset of customers is visited to fulfill the total demand, but a restriction is put on the length of each route and the number of vertices that it contains. This paper tackles a generalized variant of the m-CTP, called the multi-vehicle multi-covering Tour Problem (mm-CTP), where a vertex must be covered several times instead of once. We study a particular case of the mm-CTP considering only the restriction on the number of vertices in each route and relaxing the constraint on the length (mm-CTP-p). A hybrid metaheuristic is developet by combining Genetic Algorithm (GA), Variable Neighborhood Descent method (VND), and a General Variable Neighborhood Search algorithm (GVNS) to solve the problem. Computational experiments show that our approaches are competitive with the Evolutionary Local Search (ELS) and Genetic Algorithm (GA), the methods proposed in the literature.

scholarly journals Variable neighborhood search for minimum linear arrangement problem

2016 ◽  
Vol 26 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Nenad Mladenovic ◽  
Dragan Urosevic ◽  
Dionisio Pérez-Brito
Keyword(s):  
Variable Neighborhood Search ◽  
Optimization Problems ◽  
State Of The Art ◽  
The State ◽  
Computational Experiments ◽  
Neighborhood Search ◽  
Np Hard ◽  
Linear Arrangement ◽  
Arrangement Problem ◽  
Linear Arrangement Problem

The minimum linear arrangement problem is widely used and studied in many practical and theoretical applications. It consists of finding an embedding of the nodes of a graph on the line such that the sum of the resulting edge lengths is minimized. This problem is one among the classical NP-hard optimization problems and therefore there has been extensive research on exact and approximative algorithms. In this paper we present an implementation of a variable neighborhood search (VNS) for solving minimum linear arrangement problem. We use Skewed general VNS scheme that appeared to be successful in solving some recent optimization problems on graphs. Based on computational experiments, we argue that our approach is comparable with the state-of-the-art heuristic.

A variable neighborhood search for solving the multi-vehicle covering tour problem

2015 ◽  
Vol 47 ◽  
pp. 285-292 ◽  
Author(s):  
Manel Kammoun ◽  
Houda Derbel ◽  
Mustapha Ratli ◽  
Bassem Jarboui
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Covering Tour Problem
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