Search results for: simulated annealing algorithm

Authors: Elham Kazemi

Abstract:

Quadratic Assignment Problem (QAP) is one the combinatorial optimization problems about which research has been done in many companies for allocating some facilities to some locations. The issue of particular importance in this process is the costs of this allocation and the attempt in this problem is to minimize this group of costs. Since the QAP’s are from NP-hard problem, they cannot be solved by exact solution methods. Cuckoo Optimization Algorithm is a Meta-heuristicmethod which has higher capability to find the global optimal points. It is an algorithm which is basically raised to search a continuous space. The Quadratic Assignment Problem is the issue which can be solved in the discrete space, thus the standard arithmetic operators of Cuckoo Optimization Algorithm need to be redefined on the discrete space in order to apply the Cuckoo Optimization Algorithm on the discrete searching space. This paper represents the way of discretizing the Cuckoo optimization algorithm for solving the quadratic assignment problem.

Keywords: Quadratic Assignment Problem (QAP), Discrete Cuckoo Optimization Algorithm (DCOA), meta-heuristic algorithms, optimization algorithms

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Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

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In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

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Authors: Rafid A. Al-Khannak, Fawzi M. Al-Naima

Abstract:

Power load is one of the most important controlling keys which decide power demands and illustrate power usage to shape power market. Hence, power load forecasting is the parameter which facilitates understanding and analyzing all these aspects. In this paper, power load forecasting is solved under MATLAB environment by constructing a neural network for the power load to find an accurate simulated solution with the minimum error. A developed algorithm to achieve load forecasting application with faster technique is the aim for this paper. The algorithm is used to enable MATLAB power application to be implemented by multi machines in the Grid computing system, and to accomplish it within much less time, cost and with high accuracy and quality. Grid Computing, the modern computational distributing technology, has been used to enhance the performance of power applications by utilizing idle and desired Grid contributor(s) by sharing computational power resources.

Keywords: DeskGrid, Grid Server, idle contributor(s), grid computing, load forecasting

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Authors: Yu-Ting Wang, Yun-Hsiang Cheng, Chien-Cheng Lin, Kun-Lin Lin

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Using a transient liquid phase method, Al was successfully bonded with Al₂O₃, which deposited Ni, Cu, Ge, and Si at the surface of the Al₂O₃ substrate after annealing at the relatively low melting point of Al. No reaction interlayer existed at the interface of any Al/Al₂O₃ specimens. Al−Fe intermetallic compounds, such as Al₉Fe₂ and Al₃Fe, formed in the Al substrate because of the precipitation of Fe, which was an impurity of the Al foil, and the reaction with Al at the grain boundaries of Al during annealing processing. According to the evaluation results of mechanical and thermal properties, the Al/Al₂O₃ specimen deposited on the Ni film possessed the highest shear strength, thermal conductivity, and bonding area percentage, followed by the Cu, Ge, and Si films. The properties of the Al/Al₂O₃ specimens deposited with Ge and Si were relatively unsatisfactory, which could be because the deposited amorphous layers easily formed oxide, resulting in inferior adhesion between Al and Al₂O₃. Therefore, the optimal choice for use in high-power devices is Al/Al₂O₃, with the deposition of Ni film.

Keywords: direct-bonded aluminum, transient liquid phase, thermal conductivity, microstructures, shear strength

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Authors: Medani Khaled Ben Oualid

Abstract:

Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

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Authors: Chaghoub Soraya, Zhang Xiaoyan

Abstract:

This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.

Keywords: approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median

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Authors: Mario Robinson, Moe Rabea

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This research examines the effects of heat treatment processes on the mechanical properties and corrosion resistanceof1045 and 4140 Steel Alloysfor industrial applications. Heat treatment processes of full annealing, normalizing, quenching, and tempering are carried out on the alloy samples. The mechanical and corrosion resistance tests of the heat treated samples are carried out, and the results obtained are related to their SEMmorphologies analysis. The results show that the heat treatment processes have an effect on the tensile strength, impact, and a significant effect on the corrosion resistance of the alloy samples. With respect to the strain characteristics, significant improvement in the ductility of the samples is recorded in the full annealing and alloy tempered samples. Thus, for application requiring strength and ductility, such as in aerospace industries, this tempered heat treated alloy could be used. In addition, the quenched sample shows a significant improvement in hardness.

Keywords: heat treatment, corrosion resistance, steel, industrial appilcations

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

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Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: J. Kaabi, Y. Harrath

Abstract:

This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.

Keywords: flow shop scheduling, genetic algorithm, maintenance, priority rules

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Authors: Maddumage Don Sandeepa Lakshad Wimalananda, Jae-Kwan Kim, Ji-Myon Lee

Abstract:

Graphene is an extraordinary 2D material that shows superior electrical, optical, and mechanical properties for the applications such as transparent contacts. Further, chemical vapor deposition (CVD) technique facilitates to synthesizing of large-area graphene, including transferability. The abstract is describing the use of high surface free energy (SFE) and nano-scale high-density surface kinks (rough) existing Cu foil for CVD graphene growth, which is an opposite approach to modern use of catalytic surfaces for high-quality graphene growth, but the controllable rough morphological nature opens new era to fast synthesis (less than the 50s with a short annealing process) of graphene as a continuous film over conventional longer process (30 min growth). The experiments were shown that high SFE condition and surface kinks on Cu(100) crystal plane existing Cu catalytic surface facilitated to synthesize graphene with high monolayer and continuous nature because it can influence the adsorption of C species with high concentration and which can be facilitated by faster nucleation and growth of graphene. The fast nucleation and growth are lowering the diffusion of C atoms to Cu-graphene interface, which is resulting in no or negligible formation of bilayer patches. High energy (500W) Ar plasma treatment (inductively Coupled plasma) was facilitated to form rough and high SFE existing (54.92 mJm-2) Cu foil. This surface was used to grow the graphene by using CVD technique at 1000C for 50s. The introduced kink-like high SFE existing point on Cu(100) crystal plane facilitated to faster nucleation of graphene with a high monolayer ratio (I2D/IG is 2.42) compared to another different kind of smooth morphological and low SFE existing Cu surfaces such as Smoother surface, which is prepared by the redeposit of Cu evaporating atoms during the annealing (RRMS is 13.3nm). Even high SFE condition was favorable to synthesize graphene with monolayer and continuous nature; It fails to maintain clean (surface contains amorphous C clusters) and defect-free condition (ID/IG is 0.46) because of high SFE of Cu foil at the graphene growth stage. A post annealing process was used to heal and overcome previously mentioned problems. Different CVD atmospheres such as CH4 and H2 were used, and it was observed that there is a negligible change in graphene nature (number of layers and continuous condition) but it was observed that there is a significant difference in graphene quality because the ID/IG ratio of the graphene was reduced to 0.21 after the post-annealing with H2 gas. Addition to the change of graphene defectiveness the FE-SEM images show there was a reduction of C cluster contamination of the surface. High SFE conditions are favorable to form graphene as a monolayer and continuous film, but it fails to provide defect-free graphene. Further, plasma modified high SFE existing surface can be used to synthesize graphene within 50s, and a post annealing process can be used to reduce the defectiveness.

Keywords: chemical vapor deposition, graphene, morphology, plasma, surface free energy

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

Abstract:

Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz

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In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot

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Authors: Dimitri Golenko-Ginzburg

Abstract:

A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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Authors: Chyuan Haur Kao, Hsiang Chen, Yu Sheng Tsai, Chen Hao Hung, Yu Shan Lee

Abstract:

Dielectric electrolyte-insulator-semiconductor sensing membranes-based biosensors have been intensively investigated because of their simple fabrication, low cost, and fast response. However, to enhance their sensing performance, it is worthwhile to explore alternative materials, distinct processes, and novel treatments. An ISFET can be viewed as a variation of MOSFET with the dielectric oxide layer as the sensing membrane. Then, modulation on the work function of the gate caused by electrolytes in various ion concentrations could be used to calculate the ion concentrations. Recently, owing to the advancement of CMOS technology, some high dielectric materials substrates as the sensing membranes of electrolyte-insulator-semiconductor (EIS) structures. The EIS with a stacked-layer of SiO₂ layer between the sensing membrane and the silicon substrate exhibited a high pH sensitivity and good long-term stability. IGZO is a wide-bandgap (~3.15eV) semiconductor of the III-VI semiconductor group with several preferable properties, including good transparency, high electron mobility, wide band gap, and comparable with CMOS technology. IGZO was sputtered by reactive radio frequency (RF) on a p-type silicon wafer with various gas ratios of Ar:O₂ and was treated with rapid thermal annealing in O₂ ambient. The sensing performance, including sensitivity, hysteresis, and drift rate was measured and XRD, XPS, and AFM analyses were also used to study the material properties of the IGZO membrane. Moreover, IGZO was used as a sensing membrane in dielectric EIS bio-sensor structures. In addition to traditional pH sensing capability, detection for concentrations of Na+, K+, urea, glucose, and creatinine was performed. Moreover, post rapid thermal annealing (RTA) treatment was confirmed to improve the material properties and enhance the multi-analyte sensing capability for various ions or chemicals in solutions. In this study, the IGZO sensing membrane with annealing in O₂ ambient exhibited a higher sensitivity, higher linearity, higher H+ selectivity, lower hysteresis voltage and lower drift rate. Results indicate that the IGZO dielectric sensing membrane on the EIS structure is promising for future bio-medical device applications.

Keywords: dielectric sensing membrane, IGZO, hydrogen ion, plasma, rapid thermal annealing

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Authors: N. Yaiphaba, Elizabeth C. H.

Abstract:

YPO₄ nanoparticles codoped with Eu³⁺(5 at.%) and Bi³⁺(0, 1, 3, 5, 7, 10, 12, 15, 20 at.%) have been prepared in poly acrylic acid (PAA)-H₂O medium by hydrothermal synthesis by maintaining a temperature of 180oC. The crystalline structure of as-prepared and 500oC annealed samples transforms from tetragonal (JCPDS-11-0254) to hexagonal phase (JCPDS-42-0082) with increasing concentration of Bi³⁺ ions. However, 900oC annealed samples exhibit tetragonal structure. The crystallite size of the particles varies from 19-50 nm. The luminescence intensity increases at lower concentration of Bi³⁺ ions and then decreases with increasing Bi3+ ion concentrations. The luminescence intensity further increases on annealing at 500oC and 900oC. Further, 900oC annealed samples show sharp increase in luminescence intensity. Moreover, the samples follow bi-exponential decay indicating energy transfer from donor to the activator or non-uniform distribution of ions in the samples. The samples on excitation at 318 nm exhibit near white emission while at 394 nm excitation show emission in the red region. The as-prepared samples are redispersible and have potential applications in display devices, metal ion sensing, biological labelling, etc.

Keywords: charge transfer, sensitizer, activator, annealing

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Authors: Kristian Bautista, Ruben A. Idoy

Abstract:

A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: Fariborz Ahmadi, Reza Tati

Abstract:

Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Anjan Naidu

Abstract:

In this paper we first discuss the minimum spanning tree, then we use the Kruskal algorithm to obtain minimum spanning tree. Based on Kruskal algorithm we propose Kruskal algorithm to apply an application to find minimum cost applying the concept of spanning tree.

Keywords: Minimum Spanning tree, algorithm, Heuxistic, application, classification of Sub 97K90

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

Abstract:

Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Pavel Zabrodin

Abstract:

The drawback of magnesium alloys is poor plasticity, which complicates the forming. Effective way of improving the properties of the cast magnesium alloy AZ31 (3 wt. % Al, 0.8 wt. % Zn, 0.2 wt. % Mn)) is to combine hot extrusion at 350°C and equal-channel angular pressing (ECAP) at 180°C. Because of reduced grain sizes, changes in the nature of the grain boundaries, and enhancement of a texture that favors basal dislocation glide, after this kind of processing, increase yield stress and ductility. For study of the effect of microstructure on the mechanisms for plastic deformation, there is some interest in investigating the mechanical properties of the ultrafinegrained (UFG) Mg alloy at low temperatures, before and after annealing. It found that the amplitude and statistics at the low-temperature jump-like deformation the Mg alloy of dependent on microstructure. Reduction of the average density of dislocations and grain growth during annealing causing a reduction in the amplitude of the jump-like deformation and changes in the distribution of surges in amplitude. It found that the amplitude and statistics at the low-temperature jump-like deformation UFG alloy dependent on temperature of deformation. Plastic deformation of UFG alloy at a temperature of 10 K occurs uniformly - peculiarities is not observed. Increasing of the temperature of deformation from 4,2 to 0,5 K is causing a reduction in the amplitude and increasing the frequency of the jump-like deformation.

Keywords: jump-like deformation, low temperature, plasticity, magnesium alloy

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Authors: Abdelghani Boucheham, Djoudi Bouhafs, Nabil Khelifati, Baya Palahouane

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The main aim of this study is to investigate the low temperature internal gettering of manganese and chromium transition metals content in p-type multicrystalline silicon grown by Heat Exchanger Method (HEM). The minority carrier lifetime variation, the transition metal elements behavior, the sheet resistivity and the interstitial oxygen concentration after different temperatures annealing under N2 ambient were investigated using quasi-steady state photoconductance technique (QSSPC), secondary ion mass spectroscopy (SIMS), four-probe measurement and Fourier transform infrared spectrometer (FTIR), respectively. The obtained results indicate in the temperature range of 300°C to 700°C that the effective lifetime increases and reaches its maximum values of 28 μs at 500 °C and decreasing to 6 μs at 700 °C. This amelioration is due probably to metallic impurities internal gettering in the extended defects and in the oxygen precipitates as observed on SIMS profiles and the FTIR spectra. From 300 °C to 500 °C the sheet resistivity values rest unchanged at 30 Ohm/sq and rises significantly to reach 45 Ohm/sq for T> 500 °C.

Keywords: mc-Si, low temperature annealing, internal gettering, minority carrier lifetime, interstitial oxygen, resistivity

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Authors: Khaled Ben Oualid Medani, Samir Sayah

Abstract:

The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

Abstract:

A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: noise signal, pulse interference, signal power, spectrum width, detection

Procedia PDF Downloads 308