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This paper addresses the way in which heuristic algorithms can be used to solve the n-queen problem. Metaheuristics for algorithm simulated annealing, tabu search and genetic algorithm are shown, test results are demonstrated and upper bound complexity is determined. The efficiencies of algorithms are compared and their achievements are measured. D...
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... The n-queen problem is a popular searching problem that is a member of NP problems family [21,22,23]. The starting point of solving this problem is directly related to the probability of finding solution [24]. ...
In this paper, a novel bio-inspired and nature-inspired algorithm, namely
Dominion Algorithm is proposed for solving optimization tasks. The fundamental concepts and ideas which underlie the proposed algorithm is inspired from nature and based on the observation of the social structure and collective behavior of wolves pack in the real world. Several experiments were preformed to evaluate the proposed algorithm and examine the correlation between its main parameters.
... The n-queen problem is a popular searching problem that is a member of NP problems family [21,22,23]. The starting point of solving this problem is directly related to the probability of finding solution [24]. ...
In this paper, a novel bio-inspired and nature-inspired algorithm, namely Dominion Algorithm is proposed for solving optimization tasks. The fundamental concepts and ideas which underlie the proposed algorithm is inspired from nature and based on the observation of the social structure and collective behavior of wolves pack in the real world. Several experiments were preformed to evaluate the proposed algorithm and examine the correlation between its main parameters.
... The n-queen problem is a popular searching problem that is a member of NP problems family [21,22,23]. The starting point of solving this problem is directly related to the probability of finding solution [24]. ...
... The results showed that GA managed to catch multiple solutions for nth of queens. A research conducted in 2007, [2] showed that the NQP could be effectively solved via heuristic algorithms such as Simulated Annealing (SA) and Tabu Search (TS) by comparing their efficiencies and achievements [7]. In addition, Jordan and Brett [3] considered other board topologies and dimensions as the extensions of the problem to survey known results for the N-queens problem by placing N queens on an N*N chessboard [7]. ...
In this paper, a hybrid of Bat-Inspired Algorithm (BA) and Genetic Algorithm (GA) is proposed to solve N-queens problem. The proposed algorithm executes the behavior of microbats with changing pulse rates of emissions and loudness to final all the possible solutions in the initialization and moving phases. This dataset applied two metaheuristic algorithms (BA and GA) and the hybrid to solve N-queens problem by finding all the possible solutions in the instance with the input sizes of area 8*8, 20*20, 50*50, 100*100 and 500*500 on a chessboard. To find the optimal solution, consistently, ten run have been set with 100 iterations for all the input sizes. The hybrid algorithm obtained substantially better results than BA and GA because both algorithms were inferior in discovering the optimal solutions than the proposed randomization method. It also has been discovered that BA outperformed GA because it requires a reduced amount of steps in determining the solutions.
... N-Queens problem involves locating n queens on an n x n chessboard such that no queen attacks any other [2]. This problem is one of AI's complex and classic problems which classified in NP problems class [3]. On the chessboard, queens can be located in ( 2 ) different permutation [4]. ...
... Genetic algorithm like many of heuristic algorithms, does not guarantee of finding solution because choosing starting point of search and taking steps toward solution have been carried out randomly. In problems like N-Queens that its state space grows exponentially, starting point of search is directly related to the probability of finding solution [3][10] [13]. ...
... Structure of Genetic Algorithm[3] ...
Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. In the absence of specialized solution for a particular problem, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, the subproblems used based on genetic algorithm to cover this weakness. This proposed method is trying to provide partial view for genetic algorithm by locally searching the state space. This method works to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement. © 2018 Institute of Advanced Engineering and Science. All rights reserved.
... This type of computer does not exist [2] but this type of theoretical computer consist of infinite amount of asset to generate many processes depending upon the number of possible solution [2] [3]. In order to accept the problems in NP , several heuristic methods are used [3] [4]. Introduced by Gauss [5] (by taking N = 8) the N -Queens problem is about putting N -queens on an N ×N chessboard in a way such that each row and each column of the chessboard have exactly one queen and each diagonal of the chessboard have at most one queen. ...
... Erreginen problema NP-konplexua dela diogunean, problemaren soluzioa aurkitzea oso neketsua bihurtzen dela erregina kopurua handitu ahala esan nahi du. Arrazoi honegatik, problema hau askatzeko hainbat algoritmo garatu izan dira, hala nola, algoritmo heuristikoak (Martinjak & Golub, 2007), sare neuralak (Mandziuk, 2002), algoritmo ebolutiboak (Draa, Meshoul, Talbi, & Batouche, 2010) edota algoritmo genetikoak (Osaba, Carballedo, Onieva & Lopez, 2014). ...
Vivimos años en los que las tendencias emergentes en educación están tomando un papel relevante en las discusiones sobre la deriva de las instituciones de enseñanza. La inclusión de las
TIC y la proliferación de lo que se conoce bajo el nombre de m-learning conlleva repensar las formas en las que los estudiantes aprenden y los docentes enseñan. Este es un escenario convulso y
en constante cambio, pero que abre puertas a nuevas formas de hacer en educación. Un camino
hacia una educación más abierta, democrática y eficaz.
No es un camino sencillo. Con frecuencia, la rapidez con la que se producen los avances tecnológicos es más rápida que nuestra capacidad de integrar estas nuevas posibilidades en esquemas teóricos significativos y en propuestas de investigación novedosas. Las buenas prácticas y la
investigación conforman los dos ejes de esta publicación.
Relacionado con las buenas prácticas, encontraremos varios capítulos sobre diferentes experiencias innovadoras basadas en la utilización de la tecnología en los diversos niveles educativos
que conforman nuestro sistema educativo actual. El lector podrá leer y reflexionar sobre la variedad de usos que se le pueden dar a la tecnología en diversos contextos educativos y relacionado
con temas básicos y transversales que se desarrollan o se deberían trabajar en las aulas actuales y
del futuro.
Unido a esto último tampoco podemos olvidarnos de la investigación educativa con TIC, aspecto que se recoge desde diversas perspectivas en los diferentes capítulos de esta publicación.
Para poder realizar propuestas innovadoras y significativas, debemos analizar, comparar y reflexionar, por lo que la investigación rigurosa y académica se convierte en pilar fundamental para
el cambio.
... Erreginen problema NP-konplexua dela diogunean, problemaren soluzioa aurkitzea oso neketsua bihurtzen dela erregina kopurua handitu ahala esan nahi du. Arrazoi honegatik, problema hau askatzeko hainbat algoritmo garatu izan dira, hala nola, algoritmo heuristikoak (Martinjak & Golub, 2007), sare neuralak (Mandziuk, 2002), algoritmo ebolutiboak (Draa, Meshoul, Talbi, & Batouche, 2010) edota algoritmo genetikoak (Osaba, Carballedo, Onieva & Lopez, 2014). ...
Evolución del rol docente de la presencialidad a la virtualidad
... A witnessing solution can be constructed easily (Bell & Stevens, 2009) but note that the witness (a set of n queens) requires n log n bits to specify but this is not polynomial in the size of the input, which is only log n bits. The n-Queens problem has often been incorrectly called NP-hard, even in well-cited papers (Mandziuk, 1995;Martinjak & Golub, 2007;Shah-Hosseini, 2009;Nakaguchi, Kenya, & Tanaka, 1999, each with at least 29 citations). The counting version of the problem, i.e. to determine how many solutions to n-Queens there are, is sequence A000170 of the Online Encyclopedia of Integer Sequences (Sloane, 2016). ...
The n-Queens problem is to place n chess queens on an n by n chessboard so that no two queens are on the same row, column or diagonal. The n-Queens Completion problem is a variant, dating to 1850, in which some queens are already placed and the solver is asked to place the rest, if possible. We show that n-Queens Completion is both NP-Complete and #P-Complete. A corollary is that any non-attacking arrangement of queens can be included as a part of a solution to a larger n-Queens problem. We introduce generators of random instances for n-Queens Completion and the closely related Blocked n-Queens and Excluded Diagonals Problem. We describe three solvers for these problems, and empirically analyse the hardness of randomly generated instances. For Blocked n-Queens and the Excluded Diagonals Problem, we show the existence of a phase transition associated with hard instances as has been seen in other NP-Complete problems, but a natural generator for n-Queens Completion did not generate consistently hard instances. The significance of this work is that the n-Queens problem has been very widely used as a benchmark in Artificial Intelligence, but conclusions on it are often disputable because of the simple complexity of the decision problem. Our results give alternative benchmarks which are hard theoretically and empirically, but for which solving techniques designed for n-Queens need minimal or no change.
... Thus, a solution requires that no two queens share the same row, column, or diagonal. The eight queens' puzzle is an example of the more general n-queen's problem of placing n queens on an n*n chessboard [24]. From this definition, 8×8 chessboard has 64 cells where we get 8 rows and 8 columns. ...
The likelihood of soft errors increases with system complexity, reduction in operational voltages, exponential growth in transistors per chip, increases in clock frequencies and device shrinking. As the memory bit-cell area is condensed, single event upset that would have corrupted only a single bit-cell are now capable of upsetting multiple adjacent memory bit-cells per particle strike. Many of the errors occur when information is transmitted from one node to another node. Detection and correction of these errors is a must for many systems e.g. safety critical systems. To address this issue, a new approach is proposed in this paper to detect and correct multiple bit errors by using Horizontal-Vertical-Diagonal-Queen parity method (HVDQ). The experimental analysis shows the validation of the effectiveness of this approach by comparing its performance with existing approaches.
