scholarly journals Gaussian variable neighborhood search for the file transfer scheduling problem

2016 ◽  
Vol 26 (2) ◽  
pp. 173-188
Author(s):  
Zorica Drazic

This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results.

2012 ◽  
Vol 39 (9) ◽  
pp. 2206-2213 ◽  
Author(s):  
Emilio Carrizosa ◽  
Milan Dražić ◽  
Zorica Dražić ◽  
Nenad Mladenović

Author(s):  
Manel Kammoun ◽  
Houda Derbel ◽  
Bassem Jarboui

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.


2014 ◽  
Vol 41 (10) ◽  
pp. 4939-4949 ◽  
Author(s):  
João Paulo Queiroz dos Santos ◽  
Jorge Dantas de Melo ◽  
Adrião Dória Duarte Neto ◽  
Daniel Aloise

Sign in / Sign up

Export Citation Format

Share Document