A hybrid genetic-variable neighborhood search algorithm for the cell formation problem based on grouping efficacy

2013 ◽  
Vol 40 (4) ◽  
pp. 980-990 ◽  
Author(s):  
Mohammad Mahdi Paydar ◽  
Mohammad Saidi-Mehrabad
Keyword(s):  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Cell Formation ◽  
Neighborhood Search ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Neighborhood Search Algorithm ◽  
Grouping Efficacy

An Estimation of Distribution Algorithm for Part Cell Formation Problem

2012 ◽  
pp. 699-725
Author(s):  
Saber Ibrahim ◽  
Bassem Jarboui ◽  
Abdelwaheb Rebaï
Keyword(s):  
Machine Part ◽  
Cell Formation ◽  
Estimation Of Distribution Algorithm ◽  
Neighborhood Search ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Estimation Of Distribution ◽  
Exceptional Elements ◽  
Machine Groups ◽  
Grouping Efficacy

The aim of this chapter is to propose a new heuristic for Machine Part Cell Formation problem. The Machine Part Cell Formation problem is the important step in the design of a Cellular Manufacturing system. The objective is to identify part families and machine groups and consequently to form manufacturing cells with respect to minimizing the number of exceptional elements and maximizing the grouping efficacy. The proposed algorithm is based on a hybrid algorithm that combines a Variable Neighborhood Search heuristic with the Estimation of Distribution Algorithm. Computational results are presented and show that this approach is competitive and even outperforms existing solution procedures proposed in the literature.

An Estimation of Distribution Algorithm for Part Cell Formation Problem

2013 ◽  
pp. 164-188
Author(s):  
Saber Ibrahim ◽  
Bassem Jarboui ◽  
Abdelwaheb Rebaï
Keyword(s):  
Machine Part ◽  
Cell Formation ◽  
Estimation Of Distribution Algorithm ◽  
Neighborhood Search ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Estimation Of Distribution ◽  
Exceptional Elements ◽  
Machine Groups ◽  
Grouping Efficacy

The aim of this chapter is to propose a new heuristic for Machine Part Cell Formation problem. The Machine Part Cell Formation problem is the important step in the design of a Cellular Manufacturing system. The objective is to identify part families and machine groups and consequently to form manufacturing cells with respect to minimizing the number of exceptional elements and maximizing the grouping efficacy. The proposed algorithm is based on a hybrid algorithm that combines a Variable Neighborhood Search heuristic with the Estimation of Distribution Algorithm. Computational results are presented and show that this approach is competitive and even outperforms existing solution procedures proposed in the literature.

A variable neighborhood search algorithm for optimal protection coordination of power systems

2021 ◽  
Author(s):  
H. R. E. H. Bouchekara ◽  
M. S. Shahriar ◽  
M. S. Javaid ◽  
Y. A. Sha’aban ◽  
M. Zellagui ◽  
...  
Keyword(s):  
Power Systems ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Neighborhood Search Algorithm ◽  
Optimal Protection

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.

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