Cuckoo Search Algorithm: Statistical-Based Optimization Approach and Engineering Applications

2020 ◽  
pp. 79-99
Author(s):  
Thanh-Phong Dao
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Approach ◽  
Engineering Applications

Discrete Non-Integer Order Differentiator Models Using Moth-Flame Optimization Algorithm

2017 ◽  
Vol 261 ◽  
pp. 394-401 ◽  
Author(s):  
Shibendu Mahata ◽  
Suman Kumar Saha ◽  
Rajib Kar ◽  
Durbadal Mandal
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Mapping Function ◽  
Cuckoo Search ◽  
Simplex Algorithm ◽  
Cuckoo Search Algorithm ◽  
Optimization Approach ◽  
Integer Order ◽  
Domain Mapping ◽  
Moth Flame Optimization Algorithm

Discrete rational approximation models to the non-integer order differentiator sλ, where λ ε (0, 1), using Moth-Flame Optimization (MFO) algorithm is proposed in this paper. The proposed metaheuristic optimization approach used to design the discrete non-integer order differentiators (DNODs) does not employ any s-to-z domain mapping function to perform the discretization operation. Frequency domain characteristics of DNODs, solution reliability, and algorithm convergence performances are investigated among MFO and an advanced evolutionary algorithm called Particle Swarm Optimization with adaptive inertia weight (PSO-w). Results demonstrate the effectiveness of MFO in outperforming PSO-w in solving this non-linear and multimodal optimization problem. The proposed DNODs also exhibit better performance in comparison with the designs based on techniques such as Nelder-Mead Simplex algorithm and Cuckoo Search Algorithm published in recent literature.

scholarly journals Cuckoo Search Algorithm Optimization Approaches for Solving Economic Load Dispatch: A Review

2018 ◽  
pp. 1-15 ◽  
Author(s):  
Ganiyu Adedayo Ajenikoko ◽  
Olusoji Simeon Olaniyan ◽  
John Oludayo Adeniran
Keyword(s):  
Power Systems ◽  
Power System ◽  
Search Algorithm ◽  
Low Cost ◽  
Electrical Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Operation ◽  
Economic Load Dispatch ◽  
Optimization Approach

Cuckoo search algorithm (CSA) is an effective and highly reliable swarm intelligence based optimization approach. It is a technique of determining the most efficient, low cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. This paper presents a comprehensive review of CSA application in Economic Load Dispatch (ELD) problem. This review will assist power system engineers with a view to enhancing the optimal operation of available thermal plants in electrical power systems.

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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