GENETIC ALGORITHM IEEE PAPERS AND PROJECTS-2020



A genetic algorithm is a search heuristic that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.



Multiple criteria decision-making for hospital location-allocation based on improved genetic algorithm
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Hospital site selection is an essential problem in all societies, and the allocation of the population to these centers are included as the important optimization issues to be considered in urban planning. The present paper aims at improving the genetic algorithm by We present a novel genetic algorithmbased approach for the compact representation of heterogeneous, optically thick, translucent materials. Utilizing genetic optimization, we also find the best transformation to represent measured subsurface scattering data. We employ a Feature selection is one of the hottest machine learning topics in recent years. The main purposes of it are to simplify the original model, improve the readability of the model, and prevent over-fitting by searching for a suitable subset of features. There are many methods

Traveling Salesman Problem Solution using Genetic Algorithm
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Artificial intelligence is significantly increased with technological advancements. It can be seen in many applications of artificial intelligence in technological development. Many artificial intelligence technologies solve cases. One of the problems that can be solved by As a key technology of cloud computing, virtualization technology enables multiple virtual machines (VMs) to run on a host to meet the operational needs and environmental requirements of different applications, improving the efficiency of the host. However, the

Genetic algorithm hybridized with multilayer perceptron to have an economical slope stability design
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The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training

Routing using genetic algorithm in a wireless sensor network
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In this paper we probe the routing algorithm that maximizes the quality of the network. In this regard, we present various scenarios for comparisons among different routing algorithms in a wireless sensor network. Using simulations conducted in NS- we compare the

Workflow balancing in a speed frame assembly shop floor operations through genetic algorithm
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The assembly planning of speed frame, a textile machine involves allocation of operations to cross trained operators. The assignment of assembly operations to the operators is modeled into a parallel machine scheduling problem with precedence constraints using the objective

Evaluation Performance of SVR Genetic Algorithm and Hybrid PSO in Rainfall Forecasting
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Climate is an essential natural factor which is dynamic and challenging to predict. The accurate climate prediction is needed. In this paper, we use support vector regression (SVR) with different kernels such as polynomial, sigmoid and RBF. At the same time, we employ Recently, many researchers have paid attention to wireless sensor networks (WSNs) due to their ability to encourage the innovation of the IT industry. Although WSN provides dynamically scalable solutions with various smart applications, the growing need to Local search algorithms are widely applied in solving large-scale Distributed constraint optimization problems (DCOPs) where each agent holds a value assignment to its variable and iteratively makes a decision on whether to replace its assignment according to its

A biased random-key genetic algorithm for routing and wavelength assignment under a sliding scheduled traffic model
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The problem of routing and wavelength assignment in optical networks consists in minimizing the number of wavelengths that are needed to route a set of demands, such that demands routed using lightpaths that share common links are assigned to different Gate diffusion input (GDI) method using a simple cell makes it possible to design low-power logic gates with reduced chip area and less complexity. In this work, a novel design of single- bit optimized reversible logic-based magnitude arithmetic unit (RMAU) circuit, using Failure credibility is popular in measuring safety degree of structure under fuzzy uncertainty due to its excellent property of self-duality. Existing methods for estimating failure credibility can be mainly divided into two categories, ie, the simulation-based methods and the This paper proposes an Automatic Clustering algorithm for Interval data using the Genetic algorithm (ACIG). In this algorithm the overlapped distance between intervals is applied to determining the suitable number of clusters. Moreover, to optimize in clustering, we modify In this study response surface methodology (RSM), artificial neural network (ANN) and non- dominated sorting genetic algorithmII (NSGA-II) were used for modeling and multi objective optimization of Newbouldia Laevies Fibre and recycled high density polyethylene (RHDPE)We here present AutoGrow an open-source program for semi-automated computer-aided drug discovery. AutoGrow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of pre-enumerated compounds. It is a useful tool for Because of being imprecision and existence of uncertainty in input variables to fuzzy systems, and also their easy implementation, fuzzy controllers are introduced as one of useful optimization tools in industry especially in DC motors. Given to the growth of controller

Improving Quadrupedal Locomotion on Granular Material Using Genetic Algorithm
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This paper describes process of generating a stable gait for a quadruped robot on granular material such as sand. To achieve this goal a simulated environment was created, to model the kinematics and dynamics of the robot. Genetic algorithm was used as a gait generation Hospital cost analysis (HCA) becomes a key topic and forefront of politics, social welfare and medical discourse. HCA includes a wide range of expenses; yet the foremost attention relates to the money expense in which hospital managers would like to draw a figure ofBackground The number of porcine Single Nucleotide Polymorphisms (SNPs) used in genetic association studies is very large, suitable for statistical testing. However, in breed classification problem, one needs to have a much smaller porcine-classifying SNPs Nowadays, we live an unprecedented evolution in cloud computing technology that coincides with the development of the vast amount of complex interdependent data which make up the scientific workflows. All these circumstances developments have made the In the process of ultrasound elastic image detection of pulmonary nodules, due to various factors, the detection process of nodules will produce less sensitive and higher false positives, which will affect the detection accuracy of nodules. In order to improve the In the ensemble feature selection method, if the weight adjustment is performed on each feature subset used, the ensemble effect can be significantly different; therefore, how to find the optimized weight vector is a key and challenging problem. Aiming at this optimization One of the engineering researches is improving the devises performance. In fact, after the devises are designed, optimization is necessary to obtain more performance, less cost and fast turnaround production. In this research, the single-and multi-objective genetic Multiple sequence alignment (MSA) is characterized as a very high computational complex problem. Therefore, MSA problem cannot be solved by exhaustive methods. Nowadays, MSA is being solved by optimizing more than one objective simultaneously. In this paper, we An accurate method based on evolutionary correlation filtering to solve pose estimation of highly occluded targets is presented. The proposed method performs multiple correlation operations between an input scene and a bank of filters designed in frequency-domain

Solving the Traveling Salesman Problem using Greedy Sequential Constructive Crossover in a Genetic Algorithm
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The efficiency of genetic algorithms (GAs) depends mainly on crossover operator. The choice of good crossover operators leads to effective GA. There are many existing crossover operators in the literature. In this paper, we propose a modified version of sequential In this paper, a novel vision assisted genetic algorithm based navigational controller has been designed for smooth and collision-free path generation of a humanoid robot. Here, sensory information regarding the nearest obstacle distance and path left to the destination

Estimating WCET using prediction models to compute fitness function of a genetic algorithm
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Genetic algorithms can be used to generate input data in a real-time system that produce the worst-case execution time of a task. While generating the test data, the fitness function is normally evaluated using a cycle-accurate simulator of the processor architecture, which With the rapid growth of Internet-of-Things (IoT) applications, data volumes have been considerably increased. The processing resources of IoT nodes cannot cope with such huge workloads. Processing parts of the workload in clouds could solve this problem, but the The current clinical diagnosis of peripheral lung cancer is affected by many factors, which leads to certain uncertainty in the diagnosis results. In order to improve the clinical diagnosis of peripheral lung cancer, based on genetic algorithm this study constructs a proprietary In wire arc additive manufacturing (WAAM), deposition of multiple beads in multiple layers is required for fabricating any component. This article presents ways to optimize the selection of parameters for near-net shape deposition to minimize void and excess material in WAAM Yingtan is a rapidly urbanizing city in Jiangxi Province, South China. During rapid urbanization, construction land is expanded at the expense of cropland and forest. Although economic benefits are gained, ecological and environmental damage is irreversible. In this A simple solution of simultaneous non-linear equations is one of the most important tasks in the analysis of the systems used in different domains of engineering, social sciences, and medical sciences. Though there are many conventional methods to solve these equationsThe most important issue in computer world are security, integrity and, confidentiality, in any organizations data, for that the secret messages must be encrypted when it is transmitted. Encryption is a tool for protecting and securing data. The paper proposes a new encryption Modern embedded systems must have high reliability and performance. They should be able to tolerate both hard as well as soft errors occurring in the resources constituting the system. Reliability must be part of the system design and the system must consist of non

RSA PUBLIC KEY SOLVING TECHNIQUE BY USING GENETIC ALGORITHM
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ABSTRACT The Rivest Shamir Adleman (RSA) algorithm is one of the cryptographic algorithms that have a high level of security in the message security, and this is due to the difficulty of finding the prime number factor of a huge integer (factor n being the two main

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem
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A crossover operator is one of the critical procedures in genetic algorithms. It creates a new chromosome from the mating result to an extensive search space. In the course timetabling problem, the quality of the solution is evaluated based on the hard and soft constraints. The Purpose Femoral neck fracture (FNF) is one of the most observed orthopedic injuries in elderly patients with accompanying osteoporosis, while treatment process could be highly troublesome in young patients. Therefore, it is necessary to apply a strong fixation to theWireless sensor networks are widely used in monitoring and managing environmental factors like air quality, humidity, temperature, and pressure. The recent works show that clustering is an effective technique for increasing energy efficiency, traffic load balancing The cooperative multiple task assignment problem (CMTAP) of heterogeneous fixed-wing unmanned aerial vehicles (UAVs) performing the Suppression of Enemy Air Defense (SEAD) mission against multiple ground stationary targets is studied in this paper. The

Adaptive Sequential Constructive Crossover Operator in a Genetic Algorithm for Solving the Traveling Salesman Problem
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Genetic algorithms are widely used metaheuristic algorithms to solve combinatorial optimization problems that are constructed on the survival of the fittest theory. They obtain near optimal solution in a reasonable computational time, but do not guarantee the GA-based and conventional derivative-based inversion methods were employed to determine V s profile of subsurface soil layers from array microtremors for two cities in Iran. The applied methods were verified against geotechnical and geophysical data. The results

Fingerprint recognition based on shark smell optimization and genetic algorithm
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The rapid enhancement of technology and electronically life raised the need for an extra level of security. Security is an increasing necessity throughout the globe because a lack of security can result in great damage. Security is well-defined as the degree of resistance to

Genetic Algorithm model and data files to assess JONSWAP spectra coefficients: MATLAB code
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journal homepage: www.elsevier.com/locate/dib Data Article Genetic Algorithm model and data files to assess JONSWAP spectra coefficients: MATLAB code 70 (2020) 561 571 Robust point target detection of infrared clutter background has drawn great interest of scholars. Recently, morphological filter is playing a significant role in detecting infrared point target. Generally, the background clutter and targets are diverse in the case of each image A Roman dominating function (RDF) on a graph G is a labelling f: V→{0, 2} such that every vertex labelled 0 has at least one neighbour with label 2. The weight of G is the sum of the labels assigned. Roman domination number (RDN) of G, denoted by γR (G), is the

Design of an Efficient Concept Based Model Using Genetic Algorithm in Document Clustering
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Due to the rapid growth of information being generated on various internet sources, the effective knowledge extraction of data has become challenging. The problem of the unstructured format of the textual data is enhancing this challenge. Although, many This paper presents a novel genetic algorithm for globally solving un-constraint optimization problem. In this algorithm a new real coded crossover operator is proposed firstly. Furthermore, for improving the convergence speed and the searching ability of our Drilling of cooling holes in turbine blades on difficult to machine materials like Inconel 718 has been one of the significant applications of micro-EDM. Owing to the difficulties in the contact measurement techniques, the actual side wall characteristics of micro-holes were Open wireless sensor networks (WSNs) in Internet of things (IoT) has led to many zero-day security attacks. Since intrusion detection is a key security solution, this paper presents a lightweight machine learning-based intrusion detection technique with high performance for For four-PMSM synchronization systems, the complex structure, nonlinearities and uncertainties make accurate modeling and precise control difficult to realize. This article proposes an easily realized adaptive control scheme for four-PMSM synchronization system Soccer training assisted robot system is a combination of robotics and artificial intelligence. Motion path planning is an important part of soccer training assisted robot decision system. Path planning aims to find an optimal path, complete dynamic and static obstacle avoidance The Internet is used for exchanging information. Sometimes it is required to transmit confidential data over the internet. Here the authors use image steganography to embed confidential data within a cover image. To construct the technique, this article combines the This paper presents a new fast Intelligent Programmed Genetic Algorithm (IPGA) based evolutionary optimization algorithm which requires lesser number of objective function evaluation for reaching optima. The proposed algorithm apart from using probabilistic

Genetic Algorithm for Least Cost Routing in the Network
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Routing is one of the most prime issues in network which has a notable impact on network performance and utilisation . This has made the shortest or least cost path routing an important field of research. Although there is a considerable increase in the capacity of the

A Novel Optimized QCA 4: 1 Multiplexer Circuit Using Genetic Algorithm
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With the rapid development of very large scale integration (VLSI) technology, it has became necessitate to design circuits with high operational speed with area efficiency and high device density. The quantum dot cellular automata (QCA) technology can be a very

Fuel consumption optimisation using structural equation modelling and genetic algorithm approach: The case of commercial aviation
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The main aim of this study is to develop a model for minimising fuel consumption in civil aviation. Structural equation modelling (SEM) is utilised for this purpose and the model is developed in terms of various factors that influence fuel consumption in civil aviation. Total

IDS Based on Clustering and Immunity Genetic Algorithm
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K-means cluster algorithm has good convergence rate, it strongly depends on initialization, and it can also easily be trapped in a local optimum. Global optimum can be reached with Genetic Algorithm but GA converges very slowly. Therefore this article proposed one kind

New Gene-Level Probabilistic Genetic Algorithm to Solve Multi Local Minima Problems
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Genetic Algorithms are one of the oldest evolutionary techniques that are still relevant today, along with the years, several modifications and improvements were proposed to further develop such algorithms. In this work, a new proposal is shown that consists of using a Despite the fact that the fuzzy clustering of time series based on genetic algorithm (GA) is mostly used in applications involving univariate time series, this paper presents an approach based on GA and Fuzzy C-Means (FCM) for clustering multivariate time series. EachCervical cancer is a leading gynecologic malignancy worldwide. There are still many weaknesses in the data processing system in handling risk factors for cervical cancer. This research presents optimization techniques and shows the selection of features for the best

Shell game optimization: a novel game-based algorithm
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Moreover, SGO is compared with eight optimization algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching Learning Based Optimization (TLBO), Grey Wolf Optimizer (GWO), Grasshopper Optimization AlgorithmThis paper present an innovative technique based on multi-agent genetic algorithm for optimization of a network. We unify agent system with genetic algorithm and applied to solve multi-objective problem optimization. In this algorithm an agent illustrate a candidate results

SOLUTIONS OF STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS VIA ACCELERATED GENETIC ALGORITHM
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International Journal of Science and Humanities ISSN 2394 9236 Volume Number 2 (2019), pp. 37 41 c Islamiah College Publications http://www. islamiahcollege. edu. in SOLUTIONS OF STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS VIA ACCELERATED GENETIC ALGORITHM

Tool path optimization for drilling holes using genetic algorithm
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In CNC machining operations it is essential to improve the efficiency of the machine in terms of time, energy consumption etc. Drilling a large number of holes is widely practiced machining operation in manufacturing industries like in PCB manufacturing industry. For

Particle Swarm Optimization Algorithm Combined with Genetic Algorithm Gravitational Search Algorithm and Dynamic Cauchy Mutation for Power Loss
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Abstract; In this work particle swarm optimization (PSO) algorithm has been blended with Genetic algorithm (GA), Gravitational search algorithm (GSA), and intermingled with Dynamic Cauchy mutation to solve the reactive power problem. At first PSO merged with GA

APPLYING MULTI-POPULATION GENETIC ALGORITHM TO THE DYNAMIC FLEXIBLE JOB SHOP SCHEDULING PROBLEM.
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Considering the scheduling factors such as mechanical failures and order changes in the actual production process, the dynamic flexible job shop scheduling problem has increasingly attracted the interest of researchers. The multi-population genetic algorithm

Long-lived nearby-template preimages on biometric transformation with genetic algorithm
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The use of biometric systems has exploded in recent years. The data handled there is sensitive, because biometric data cannot been changed like passwords. Several protection systems were invented to prevent biometric data recovery. The goal of biometric trans- formation is toIn this paper, derivative free optimization methods specifically Genetic Algorithm is discussed. The solution of bound-constrained optimization problems by using Genetic algorithm the concept of the project is divided into five parts: The first part is the introduction

Genetic Algorithm with Comprehensive Sequential Constructive Crossover for the Travelling Salesman Problem
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The travelling salesman problem (TSP) is a very famous NP-hard problem in operations research as well as in computer science. To solve the problem several genetic algorithms (GAs) are developed which depend primarily on crossover operator. The crossover

Implementation of the genetic algorithm in an application for solving a traveling salesman problem
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The theme of this paper is the implementation of a genetic algorithm in an application that solves the problem of a traveling salesman. The problem for the traveling salesman is the problem of finding the optimal route and returning to the point of origin. Since this problem

A Review of Crossover Methods and Problem Representation of Genetic Algorithm in Recent Engineering Applications
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Genetic algorithm (GA) is a popular technique of optimization that is bio-inspired and based on Charles Darwins proposed principles of natural genetics and natural selection theories. The algorithm operates on three simple genetic operators called selection, crossover and In this paper we focus on an unrelated parallel workgroup scheduling problem where each workgroup is composed of a number of personnel with similar work skills which has eligibility and human resource constraints. The most difference from the general unrelated

Genetic AlgorithmBased Docking of Potent Inhibitors Against SARS-CoV-2 Main Protease: A Comparison Between Natural Products and Synthetic Drugs.
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The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused coronavirus disease-2019 (COVID-19) pandemic. Despite the intensive research currently, there are no therapeutics and vaccines available. As the main protease (MPro) plays a vital

The Research on Optimization of Logistics Distribution Path Based on Genetic Algorithm
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S Wang, Z Lin 166.62.7.99 In the logistics activities, the distribution cost occupies a large proportion of the whole logistics cost, and the main factor that affects the cost is how to arrange the transportation route reasonably, so how to optimize the distribution route with reasonable methods is an