scholarly journals A new two-stage variable neighborhood search algorithm for the nurse rostering problem

2021 ◽  
Author(s):  
Mohammed Abdelghany ◽  
Zakaria Yahia ◽  
Amr B. Eltawil
Keyword(s):  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Soft Constraints ◽  
Nurse Rostering ◽  
Two Stage ◽  
Nurse Rostering Problem ◽  
Solution Methods ◽  
Np Hard Problem ◽  
Neighborhood Search Algorithm

The nurse rostering problem refers to the assignment of nurses to daily shifts according to the required demand of each shift and day, with consideration for the operational requirements and nurses’ preferences. This problem is known to be an NP-hard problem, difficult to be solved using the known exact solution methods especially for large size instances. Mostly, this problem is modeled with soft and hard constraint, and the objective is set to minimize the violations for the soft constraints. In this paper, a new two-stage variable neighborhood search algorithm is proposed for solving the nurse rostering problem. The first stage aims at minimizing the violations of the soft constraints with the higher penalty weights in the objective function. While the second stage considers minimizing the total solution penalty taking into account all the soft constraint. The proposed algorithm was tested using 24 benchmark instances. The test results revealed that the proposed algorithm is able to compete the results of a recent heuristic approach from literature for most of the tested instances.

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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