scholarly journals A Prefiltered Cuckoo Search Algorithm with Geometric Operators for Solving Sudoku Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Cristian Galleguillos ◽  
Eric Monfroy ◽  
Fernando Paredes
Keyword(s):  
Feasible Solution ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Search Algorithms ◽  
Experimental Results ◽  
Approximate Methods ◽  
Np Complete ◽  
Combinatorial Space

The Sudoku is a famous logic-placement game, originally popularized in Japan and today widely employed as pastime and as testbed for search algorithms. The classic Sudoku consists in filling a9×9grid, divided into nine3×3regions, so that each column, row, and region contains different digits from 1 to 9. This game is known to be NP-complete, with existing various complete and incomplete search algorithms able to solve different instances of it. In this paper, we present a new cuckoo search algorithm for solving Sudoku puzzles combining prefiltering phases and geometric operations. The geometric operators allow one to correctly move toward promising regions of the combinatorial space, while the prefiltering phases are able to previously delete from domains the values that do not conduct to any feasible solution. This integration leads to a more efficient domain filtering and as a consequence to a faster solving process. We illustrate encouraging experimental results where our approach noticeably competes with the best approximate methods reported in the literature.

scholarly journals An Improved Hybrid Encoding Cuckoo Search Algorithm for 0-1 Knapsack Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yanhong Feng ◽  
Ke Jia ◽  
Yichao He
Keyword(s):  
Optimization Problem ◽  
Feasible Solution ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Genetic Mutation ◽  
Cuckoo Search Algorithm ◽  
Knapsack Problems ◽  
Local Optimum ◽  
Transform Method ◽  
Continuous Space

Cuckoo search (CS) is a new robust swarm intelligence method that is based on the brood parasitism of some cuckoo species. In this paper, an improved hybrid encoding cuckoo search algorithm (ICS) with greedy strategy is put forward for solving 0-1 knapsack problems. First of all, for solving binary optimization problem with ICS, based on the idea of individual hybrid encoding, the cuckoo search over a continuous space is transformed into the synchronous evolution search over discrete space. Subsequently, the concept of confidence interval (CI) is introduced; hence, the new position updating is designed and genetic mutation with a small probability is introduced. The former enables the population to move towards the global best solution rapidly in every generation, and the latter can effectively prevent the ICS from trapping into the local optimum. Furthermore, the greedy transform method is used to repair the infeasible solution and optimize the feasible solution. Experiments with a large number of KP instances show the effectiveness of the proposed algorithm and its ability to achieve good quality solutions.

An Improve Cuckoo Search Algorithm for Traveling Salesman Problems

2014 ◽  
Vol 651-653 ◽  
pp. 2291-2295
Author(s):  
Suo Nan Lengzhi ◽  
Yue Guang Li
Keyword(s):  
Multiple Solutions ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traveling Salesman ◽  
Experimental Results ◽  
Traveling Salesman Problems ◽  
Position Value ◽  
Benchmark Instances ◽  
Simulation Results

In this paper, according to the characteristics of TSP. An improve Cuckoo Search Algorithm was used to solve the TSP, adopting the code rule of randomized key representation based on the smallest position value. The experimental results show that the new algorithm is successful in locating multiple solutions and has better accuracy, simulation results of benchmark instances validate the efficiency and superiority of Cuckoo Search Algorithm.

An Improve Cuckoo Search Algorithm for Solving Nonlinear Equation Group

2014 ◽  
Vol 651-653 ◽  
pp. 2121-2124
Author(s):  
Rui Hong Zhou ◽  
Yue Guang Li
Keyword(s):  
Nonlinear Equation ◽  
Nonlinear Equations ◽  
Multiple Solutions ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Experimental Results ◽  
Systems Of Nonlinear Equations ◽  
Equation Group

In this paper, according to the characteristics of nonlinear equations. An improve Cuckoo Search Algorithm was used to solve the systems of nonlinear equations, the algorithm was experimented and the experimental results show that the new algorithm to be successful in locating multiple solutions and better accuracy. At the end the paper made a simple comparison with the bat algorithms.

Cuckoo Search Algorithm for Solving Ill-Conditioned Linear Equations

2014 ◽  
Vol 1049-1050 ◽  
pp. 1367-1370
Author(s):  
Yu Feng Ma ◽  
Yue Guang Li
Keyword(s):  
Multiple Solutions ◽  
Search Algorithm ◽  
Linear Equations ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Experimental Results ◽  
Traditional Methods

In this paper, according to the characteristics of ill-conditioned linear equations. A Cuckoo Search Algorithm was used to solve the systems of ill-conditioned linear equations, the algorithm was experimented and the experimental results show that the algorithm to be successful in locating multiple solutions and better accuracy. At the end the paper made a simple comparison with the traditional methods..

Cuckoo Search Algorithm and its Application on School Bus Problem

2014 ◽  
Vol 687-691 ◽  
pp. 1363-1366
Author(s):  
Xiao Long Ma ◽  
Yue Guang Li
Keyword(s):  
Mathematical Model ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Experimental Results ◽  
Route Optimization ◽  
School Bus ◽  
Improved Cuckoo Search Algorithm ◽  
The Mathematical Model

In this paper, discusses the school bus problem, given the mathematical model of route optimization, put forward an improved cuckoo search algorithm. Finally, take school bus routes running problem of Gansu Normal College for Nationalities as an example, the algorithm was experimented and the experimental results show that the algorithm to be successful.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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