scholarly journals A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2611
Author(s):  
José García ◽  
José Lemus-Romani ◽  
Francisco Altimiras ◽  
Broderick Crawford ◽  
Ricardo Soto ◽  
...  
Keyword(s):  
Local Search ◽  
Knapsack Problem ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Local Search Operator ◽  
Insight Into

Optimization techniques, specially metaheuristics, are constantly refined in order to decrease execution times, increase the quality of solutions, and address larger target cases. Hybridizing techniques are one of these strategies that are particularly noteworthy due to the breadth of applications. In this article, a hybrid algorithm is proposed that integrates the k-means algorithm to generate a binary version of the cuckoo search technique, and this is strengthened by a local search operator. The binary cuckoo search algorithm is applied to the NP-hard Set-Union Knapsack Problem. This problem has recently attracted great attention from the operational research community due to the breadth of its applications and the difficulty it presents in solving medium and large instances. Numerical experiments were conducted to gain insight into the contribution of the final results of the k-means technique and the local search operator. Furthermore, a comparison to state-of-the-art algorithms is made. The results demonstrate that the hybrid algorithm consistently produces superior results in the majority of the analyzed medium instances, and its performance is competitive, but degrades in large instances.

A new hybrid cuckoo search and firefly optimization

2018 ◽  
Vol 24 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Mariam Elkhechafi ◽  
Hanaa Hachimi ◽  
Youssfi Elkettani
Keyword(s):  
Global Optimization ◽  
Hybrid Algorithm ◽  
Firefly Algorithm ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Heuristic Optimization ◽  
Firefly Optimization ◽  
New Generation

Abstract In this paper, we present a new hybrid algorithm which is a combination of a hybrid Cuckoo search algorithm and Firefly optimization. We focus in this research on a hybrid method combining two heuristic optimization techniques, Cuckoo Search (CS) and Firefly Algorithm (FA) for the global optimization. Denoted as CS-FA. The hybrid CS-FA technique incorporates concepts from CS and FA and creates individuals in a new generation not only by random walk as found in CS but also by mechanisms of FA. To analyze the benefits of hybridization, we have comparatively evaluated the classical Cuckoo Search and Firefly Algorithms versus the proposed hybridized algorithms (CS-FA).

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

scholarly journals Multilevel Image Thresholding for Image Segmentation using Hybrid Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 4272-4279
Keyword(s):  
Image Segmentation ◽  
Search Algorithm ◽  
Similarity Index ◽  
Structural Similarity ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Entropy Maximization ◽  
Image Thresholding ◽  
Segmentation Threshold

Image thresholding is an extraction method of objects from a background scene, which is used most of the time to evaluate and interpret images because of their advanced simplicity, robustness, time reduced, and precision. The main objective is to distinguish the subject from the background of the image segmentation. As the ordinary image segmentation threshold approach is computerized costly while the necessity for optimization techniques are highly recommended for multi-tier image thresholds. Level object segmentation threshold by using Shannon entropy and Fuzzy entropy maximized with hGSA-PS. An entropy maximization of hGSA-PS dependent multilevel image thresholds is developed, where the results are best demonstrated in PSNR, misclassification, structural similarity index and segmented image quality compared to the Firefly algorithm, adaptive cuckoo search algorithm and the search algorithm gravitational.

scholarly journals Cuckoo search algorithm to solve the problem of economic emission dispatch with the incorporation of facts devices under the valve-point loading effect

2021 ◽  
Vol 34 (4) ◽  
pp. 569-588
Author(s):  
Larouci Benyekhlef ◽  
Sitayeb Abdelkader ◽  
Boudjella Houari ◽  
Ayad Ahmed Nour El Islam
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Fuel Cost ◽  
Loading Effect ◽  
Facts Devices ◽  
Emission Dispatch ◽  
Valve Point Loading Effect ◽  
Economic Emission Dispatch

The essential objective of optimal power flow is to find a stable operating point which minimizes the cost of the production generators and its losses, and keeps the power system acceptable in terms of limits on the active and reactive powers of the generators. In this paper, we propose the nature-inspired Cuckoo search algorithm (CSA) to solve economic/emission dispatch problems with the incorporation of FACTS devices under the valve-point loading effect (VPE). The proposed method is applied on different test systems cases to minimize the fuel cost and total emissions and to see the influence of the integration of FACTS devices. The obtained results confirm the efficiency and the robustness of the Cuckoo search algorithm compared to other optimization techniques published recently in the literature. In addition, the simulation results show the advantages of the proposed algorithm for optimizing the production fuel cost, total emissions and total losses in all transmission lines.

scholarly journals An Optimized Model for Energy Efficiency on Cloud System using PSO & CUCKOO Search Algorithm

2019 ◽  
Vol 8 (9S) ◽  
pp. 138-144
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Programming Languages ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Google Docs ◽  
Platform As A Service ◽  
Multiple Resources

Cloud computing is one of the growing technologies, these days. Cloud computing is a paradigm that is surrounded by multiple resources, which helps in resource utilization. Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (Saas) are named as services of cloud computing. In the IaaS models, users can rent infrastructure of the data center as a service. Some of the examples of IAAS are Google Compute Engine (GCE) and Amazon Web Service (AWS). In the PaaS models, users can take services like operating system and database. Some of the examples of PAAS are Microsoft Azure and Google App Engine. In the SaaS models, users can access and install application software and databases via Internet. Examples of SAAS are Citrix GoToMeeting and Google Docs. In this paper algorithms named as PSO and CSA are discussed The objective of optimization for energy consumption on cloud has also been discussed in the paper. Along with the optimization techniques, the detailed literature reviews have been presented. To achieve the proposed work, CloudSim simulators and standard programming languages have been used. The performance of the proposed work will be analyzed by using the various performance parameters such as response time, energy efficiency and execution time.

Cuckoo search algorithm based on frog leaping local search and chaos theory

2015 ◽  
Vol 266 ◽  
pp. 1083-1092 ◽  
Author(s):  
Xueying Liu ◽  
Meiling Fu
Keyword(s):  
Local Search ◽  
Chaos Theory ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm

scholarly journals Cuckoo Search Algorithm for Congestion Alleviation with Incorporation of Wind Farm

2018 ◽  
Vol 8 (6) ◽  
pp. 4871
Author(s):  
Kaushik Paul ◽  
Niranjan Kumar
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Search Algorithm ◽  
Past Research ◽  
Cuckoo Search ◽  
Congestion Management ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Management Approach ◽  
Sensitivity Factor

The issue to alleviate congestion in the power system framework has emerged as an alluring field for the power system researchers. The research conducted in this article proposes a cuckoo search algorithm based congestion alleviation strategy with the incorporation of wind farm. The bus sensitivity factor data are computed and utilized to sort out the sutiable position for the installation of the wind farm. The generators contributing in the real power rescheduleing process are selected as per the generator sensitivity values. The cuckoo search algorithm is implemented to minimize the congestion cost with the embodiment of the wind farm.The proposed method is tested on 39 bus New England framework and the results obtained with the cuckoo search based congestion management approach outperforms the results opted with other heuristic optimization techniques in the past research literatures.

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