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The aim of the Sudoku puzzle is filling with digits from 1 to 9 into each cell of a square matrix with 9 rows and 9 columns, divided into 9 3 × 3 regions, so that each column, row, and region contains have different values. This paper reports recent results for solving Sudokus achieved by combining metaheuristics and AC3 which is a filtering technique coming from the constraint programming domain. more...

In constraint programming, efficiency in the resolution process can be affected by the order in which the variables of the problem and the domain values are selected. This activity is known as enumeration. At the beginning, it is difficult to determine the best choice variable-value pair that can generate potential solutions for constraint satisfaction problems. In this paper, we present an evaluation of different enumeration strategies, based on performance exhibited in a set indicators. These strategies solve different instances of constraint problems satisfactions. The results show that it is feasible to solve constraint satisfaction with at least one strategy enumeration. more...

This paper presents metaheuristic Shuffled Frog Leaping Algorithm (SFLA) to solve the Set Covering Problem (SCP), the SFLA is inspired by the social behavior of frogs, and is being applied to solve many optimization problems. The proposed algorithm includes eight binarization functions and discretization method for resolving the binary representation of the SCP. In the 65 instances of SCP we obtains very promising results. more...

In the present paper, we resolve the Set Covering Problem using the recently presented meta-heuristic named Binary Bat Algorithm. We use two variations of this algorithm. The Binary Bat Algorithm algorithm was created observing how the bats evade obstacles and find preys to eat, the use of echo-localization is how they do it. We made some changes using two different transfer and two discretization techniques to solve the problem. more...

The set covering problem belongs to the combinatorial optimization problems, whose complexity is exponential theoretically established as NP-complex problems. Consists in finding a subset of columns in a matrix of zeros and ones such that cover all rows of the matrix at minimal cost. The solution to this problem is presented using, for first time, the binary cat swarm optimization algorithm. This metaheuristic is based on the cat's behavior, where cats have curiosity by objects in motion and have a great hunting ability. Cats have two modes of behavior: seeking mode and tracing mode. The algorithm is tested on 65 instances, which are compared in a result table including a column with the relative percentage deviation. more...

If the meetings within the organizations properly fulfill their purposes would be of a high strategic value. However, they are often considered as inefficient and ineffective. The organizations invest time and resources in improving their productions and organizational processes but not in optimizing their meetings. When they do so, usually they do not get the results expected. At first glance, it seems an issue of an easy solution but it is not, because it is connected to the complexity of human beings. The traditional conception associates a meeting with a time or physical space where issues that are in a list of topics are addressed. Through the proposal that we have successfully worked in the organizations we outline that the meetings are rites of conversational networks and organizational processes. This understanding opens a wide range of possibilities and opportunities of optimization. more...

In this paper, we propose a Modified Binary Firefly Algorithm to solve different instances of the Set Covering Problem (SCP). The Set Covering Problem is considered a classic combinatorial optimization problem, belonging to the class NP-hard problem [8] and have many practical applications. In this paper we consider applying Modified Binary Firefly Algorithm supported in eight Transfer Functions and five Discretization Methods that allow us to express the solution of the problem in the binary domain. The different results presented in this paper show that our algorithm is a good alternative at a low cost to solve the SCP. more...

The Set Covering Problem (SCP) is a representation of a kind of combinatorial optimization problem which has been applied in several problems in the real world. In this work is used the binary version of Teaching-Learning-Based Optimization algorithm (TLBO), which works with two phases known as teacher and learner phases in this way emulates the behaviour into a classroom, besides this problem is solved with eight different transfer functions and five discretization methods all of them altogether to solve The Set Covering Problem from the OR-Library. more...

The goal of this work is to reveal the discursive strategies that employ the digital platform of a Chilean mass media to represent the female gender and the corresponding people interaction on social networks with respect to the news. This is important because if we can detect the existence of male hegemony, we could conclude that it is a prevailing ideology and thus corroborate the existence of a patriarchal order in the national press. We take as a starting point that mass media constitute a privileged access platform, because through language they spread a particular world vision, even though the press — as publicly representation — intend to accommodate a wide and heterogeneous set of speeches. The mass media, as active agents in social processes, target imagined, massive, and diverse audiences, because through its discourse, they present fragments and perspectives of the “reality” with which hide, describe, make visible, ignore or reinforce constructions and ideologies. When analyzing the modes of representation of the female gender, we observe how they refer to the women, generating an important and motivating challenge that will allow us to detect and describe how the subordination of the female gender is manifested in a particular social time. more...

Many practical applications are used in set covering problems (SCP), in this research, we used to solve SCP: the binary Fruit Fly Optimization algorithms. This algorithm is divided in four phases: initiation, smell based search local vision based search and global vision based search. The metaheuristic is based by the knowledge from the foraging behavior of fruit-flies in finding food. The algorithm used a probability vector to improve the exploration. The tests were performed with eight different transfer functions and an elitist selection method. The test results show the effectiveness of the algorithm proposed. more...

Cuckoo search is a modern bio-inspired metaheuristic that has successfully been used to solve different real world optimization problems. In particular, it has exhibited rapid convergence reaching considerable good results. In this paper, we employ this technique to solve the set covering problem, which is a well-known optimization benchmark. We illustrate interesting experimental results where the proposed algorithm is able to obtain several global optimums for different set covering instances from the OR-Library. more...