Search results for: multi-objective combinatorial optimization problem

Authors: Myeong-Gon Lee, Yang-Gyun Kim, Tae-Young Kim, Seung-Ho Han

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The high-pressure valve uses one set of 2-way valves for the purpose of reversing fluid direction. If there is no accurate control device for the 2-way valves, lots of surging can be generated. The surging is a kind of pressure ripple that occurs in rapid changes of fluid motions under inaccurate valve control. To reduce the surging effect, a 3-way reversing valve can be applied which provides a rapid and precise change of water flow directions without any accurate valve control system. However, a cavitation occurs due to a complicated internal trim shape of the 3-way reversing valve. The cavitation causes not only noise and vibration but also decreasing the efficiency of valve-operation, in which the bubbles generated below the saturated vapor pressure are collapsed rapidly at higher pressure zone. The shape optimization of the 3-way reversing valve to minimize the cavitation effect is necessary. In this study, the cavitation index according to the international standard ISA was introduced to estimate macroscopically the occurrence of the cavitation effect. Computational fluid dynamic analysis was carried out, and the cavitation effect was quantified by means of the percent of cavitation converted from calculated results of vapor volume fraction. In addition, the shape optimization of the 3-way reversing valve was performed by taking into account of the percent of cavitation.

Keywords: 3-Way reversing valve, cavitation, shape optimization, vapor volume fraction

Procedia PDF Downloads 371

Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

Procedia PDF Downloads 324

Authors: Chung To Kong, Siu Ming Yiu

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Rubik's cube was invented in 1974. Since then, speedcubers all over the world try their best to break the world record again and again. The newest record is 3.47 seconds. There are many factors that affect the timing, including turns per second (tps), algorithm, finger trick, hardware of the cube. In this paper, the lower bound of the cube solving time will be discussed using convex optimization. Extended analysis of the world records will be used to understand how to improve the timing. With the understanding of each part of the solving step, the paper suggests a list of speed improvement techniques. Based on the analysis of the world record, there is a high possibility that the 3 seconds mark will be broken soon.

Keywords: Rubik's Cube, speed, finger trick, optimization

Procedia PDF Downloads 207

Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

Procedia PDF Downloads 140

Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

Procedia PDF Downloads 246

Authors: Sukant Mehra, Parth Gupta, Varun Arora, Sarvoday Singh, Amit Kohli

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The study was emphasised on dry sliding wear behavior of AISI 1042 steel. Dry sliding wear tests were performed using pin-on-disk apparatus under normal loads of 5, 7.5 and 10 kgf and at speeds 600, 750 and 900 rpm. Response surface methodology (RSM) was utilized for finding optimal values of process parameter and experiment was based on rotatable, central composite design (CCD). It was found that the wear followed linear pattern with the load and rpm. The obtained optimal process parameters have been predicted and verified by confirmation experiments.

Keywords: central composite design (CCD), optimization, response surface methodology (RSM), wear

Procedia PDF Downloads 577

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Badr Alkahtani

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In this poster, numerical solutions of two-dimensional and three-dimensional lid driven cavity are presented by solving the steady Navier-Stokes equations at high Reynolds numbers where it becomes difficult. Lid driven cavity is where the a fluid contained in a cube and the upper wall is moving. In two dimensions, we use the streamfunction-vorticity formulation to solve the problem in a square domain. A numerical method is employed to discretize the problem in the x and y directions with a spectral collocation method. The problem is coded in the MATLAB programming environment. Solutions at high Reynolds numbers are obtained up to Re=20000 on a fine grid of 131 * 131. Also in this presentation, the numerical solutions for the three-dimensional lid-driven cavity problem are obtained by solving the velocity-vorticity formulation of the Navier-Stokes equations (which is the first time that this has been simulated with special boundary conditions) for various Reynolds numbers. A spectral collocation method is employed to discretize the y and z directions and a finite difference method is used to discretize the x direction. Numerical solutions are obtained for Reynolds number up to 200. , The work prepared here is to show the efficiency of methods used to simulate the physical problem where accurate simulations of lid driven cavity are obtained at high Reynolds number as mentioned above. The result for the two dimensional problem is far from the previous researcher result.

Keywords: lid driven cavity, navier-stokes, simulation, Reynolds number

Procedia PDF Downloads 715

Authors: K. A. Razhiyah

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Disruptive behavior is a problem that is usually associated with those with autism. There is a need to overcome this behavioral problem because the negative impact of this problem does not only effect the social relation of the students but also can cause uneasiness to those around them. This condition will be worse if the techniques used failed to motivate students to change the behaviour. The purpose of this study was to determine the effect of the circus games technique on the disruptive behavior amongst students with autism. The positive results of the intervention that was carried out for three months show the reduction in disruptive behaviour, and also improvement in the turn-taking and focusing ability aspect. Positive changes shown by the students had an encouraging effect and in a way are helping them in the teaching and learning process.

Keywords: autism, desruptive behaviour, circus, effect

Procedia PDF Downloads 248

Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

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Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

Procedia PDF Downloads 265

Authors: Zahra Ranjbar

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Interpretive structural modeling (ISM) is a well-established methodology for identifying relationships among specific variables, which define a problem or an issue. In this study most important variables that have critical role in children obesity problem were introduce by ISM questionnaire technique and their relationships were determine. Our findings suggested that sedentary activities are top level variables and school teachers and administrators, public education and scientific collaborations are bottom level variables in children obesity problem. Control of dietary, Physical education program, parents, government and motivation strategies variables are depend to other variables. They are very sensitive to external variables. Also, physical education program, parents, government, motivation, school teachers and administrators, public education and collaboration variables have strong driving power. They are linkage factors; it means that they can be effective on children obesity problem directly.

Keywords: ISM, variable, obesity, physical education, children

Procedia PDF Downloads 456

Authors: Amruta Rout, Golak Bihari Mahanta, Gunji Bala Murali, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications.

Keywords: robotic arc welding, weld process parameters, weld joint parameters, principal component analysis, fuzzy logic, Taguchi method

Procedia PDF Downloads 179

Authors: Wen-Bao Qiao, Jean-Charles Créput

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To accelerate the solution for large scale traveling salesman problems (TSP), a parallel 2-opt local search algorithm with simple implementation based on Graphics Processing Unit (GPU) is presented and tested in this paper. The parallel scheme is based on technique of data decomposition by dynamically assigning multiple K processors on the integral tour to treat K edges’ 2-opt local optimization simultaneously on independent sub-tours, where K can be user-defined or have a function relationship with input size N. We implement this algorithm with doubly linked list on GPU. The implementation only requires O(N) memory. We compare this parallel 2-opt local optimization against sequential exhaustive 2-opt search along integral tour on TSP instances from TSPLIB with more than 10000 cities.

Keywords: parallel 2-opt, double links, large scale TSP, GPU

Procedia PDF Downloads 625

Authors: Pushpendra S. Bharti, S. Maheshwari

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Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: electric discharge machining, material removal rate, surface roughness, too wear rate, multi-response signal-to-noise ratio, multi response signal-to-noise ratio, optimization

Procedia PDF Downloads 354

Authors: Bingxi Huang, Yiqing Li, Marek Morzynski, Bernd R. Noack

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We propose a Kriging-based global optimization method for active flow control with multiple actuation parameters. This method is designed to converge quickly and avoid getting trapped into local minima. We follow the model-free explorative gradient method (EGM) to alternate between explorative and exploitive steps. This facilitates a convergence similar to a gradient-based method and the parallel exploration of potentially better minima. In contrast to EGM, both kinds of steps are performed with Kriging surrogate model from the available data. The explorative step maximizes the expected improvement, i.e., favors regions of large uncertainty. The exploitive step identifies the best location of the cost function from the Kriging surrogate model for a subsequent weight-biased linear-gradient descent search method. To verify the effectiveness and robustness of the improved Kriging-based optimization method, we have examined several comparative test problems of varying dimensions with limited evaluation budgets. The results show that the proposed algorithm significantly outperforms some model-free optimization algorithms like genetic algorithm and differential evolution algorithm with a quicker convergence for a given budget. We have also performed direct numerical simulations of the fluidic pinball (N. Deng et al. 2020 J. Fluid Mech.) on three circular cylinders in equilateral-triangular arrangement immersed in an incoming flow at Re=100. The optimal cylinder rotations lead to 44.0% net drag power saving with 85.8% drag reduction and 41.8% actuation power. The optimal results for active flow control based on this configuration have achieved boat-tailing mechanism by employing Coanda forcing and wake stabilization by delaying separation and minimizing the wake region.

Keywords: direct numerical simulations, flow control, kriging, stochastic optimization, wake stabilization

Procedia PDF Downloads 106

Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

Procedia PDF Downloads 122

Authors: Vinay A. Sharma, Shiva Prasad H. C.

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The initial stages of any project are often observed to be in a mixed set of conditions. Setting up the project is a tough task, but taking the initial decisions is rather not complex, as some of the critical factors are yet to be introduced into the scenario. These simple initial decisions potentially shape the timeline and subsequent events that might later be plotted on it. Proceeding towards the solution for a problem is the primary objective in the initial stages. The optimization in the solutions can come later, and hence, the resources deployed towards attaining the solution are higher than what they would have been in the optimized versions. A ‘logic’ that counters the problem is essentially the core of the desired solution. Thus, if the problem is solved, the deployment of resources has led to the required logic being attained. As the project proceeds along, the individuals working on the project face fresh challenges as a team and are better accustomed to their surroundings. The developed, optimized solutions are then considered for implementation, as the individuals are now experienced, and know better of the consequences and causes of possible failure, and thus integrate the adequate tolerances wherever required. Furthermore, as the team graduates in terms of strength, acquires prodigious knowledge, and begins its efficient transfer, the individuals in charge of the project along with the managers focus more on the optimized solutions rather than the traditional ones to minimize the required resources. Hence, as time progresses, the authorities prioritize attainment of the required logic, at a lower amount of dedicated resources. For empirical analysis of the stated theory, leaders and key figures in organizations are surveyed for their ideas on appropriate logic required for tackling a problem. Key-pointers spotted in successfully implemented solutions are noted from the analysis of the responses and a metric for measuring logic is developed. A graph is plotted with the quantifiable logic on the Y-axis, and the dedicated resources for the solutions to various problems on the X-axis. The dedicated resources are plotted over time, and hence the X-axis is also a measure of time. In the initial stages of the project, the graph is rather linear, as the required logic will be attained, but the consumed resources are also high. With time, the authorities begin focusing on optimized solutions, since the logic attained through them is higher, but the resources deployed are comparatively lower. Hence, the difference between consecutive plotted ‘resources’ reduces and as a result, the slope of the graph gradually increases. On an overview, the graph takes a parabolic shape (beginning on the origin), as with each resource investment, ideally, the difference keeps on decreasing, and the logic attained through the solution keeps increasing. Even if the resource investment is higher, the managers and authorities, ideally make sure that the investment is being made on a proportionally high logic for a larger problem, that is, ideally the slope of the graph increases with the plotting of each point.

Keywords: decision-making, leadership, logic, strategic management

Procedia PDF Downloads 108

Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Tahri Toufik, Bouchachia Mohamed, Braikia Oussama

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The objective of this work is the design and optimization of a hybrid PV-Diesel-Wind power system with storage in order to power a relay antenna telecommunication isolated in Chlef region. The aim of the simulation of this hybrid system by the HOMER software is to determine the size and the number of each element of the system and to determine the optimal technical and economic configuration using monthly average values per year for a fixed charge antenna relay telecommunication of 22kWh/d.

Keywords: HOMER, hybrid, PV-diesel-wind system, relay antenna telecommunication

Procedia PDF Downloads 518

Authors: Azim Khodadadi, Sahar Sadaat Vakili, Ebrahim Babaei

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This study presents a numerical method to optimize the failure rate and repair time of a typical radial distribution system. Failure rate and repair time are effective parameters in customer and energy based indices of reliability. Decrease of these parameters improves reliability indices. Thus, system stability will be boost. The penalty functions indirectly reflect the cost of investment which spent to improve these indices. Constraints on customer and energy based indices, i.e. SAIFI, SAIDI, CAIDI and AENS have been considered by using a new method which reduces optimization algorithm controlling parameters. Imperialist Competitive Algorithm (ICA) used as main optimization technique and particle swarm optimization (PSO), simulated annealing (SA) and differential evolution (DE) has been applied for further investigation. These algorithms have been implemented on a test system by MATLAB. Obtained results have been compared with each other. The optimized values of repair time and failure rate are much lower than current values which this achievement reduced investment cost and also ICA gives better answer than the other used algorithms.

Keywords: imperialist competitive algorithm, failure rate, repair time, radial distribution network

Procedia PDF Downloads 669

Authors: Deepak Kumar, Jahangeer, Brijesh Kumar Yadav, Shashi Mathur

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In-situ remediation is a technique which can remediate either surface or groundwater at the site of contamination. In the present study, simulation optimization approach has been used to develop management strategy for remediating LNAPL (Light Non-Aqueous Phase Liquid) contaminated aquifers. Benzene, toluene, ethyl benzene and xylene are the main component of LNAPL contaminant. Collectively, these contaminants are known as BTEX. In in-situ bioremediation process, a set of injection and extraction wells are installed. Injection wells supply oxygen and other nutrient which convert BTEX into carbon dioxide and water with the help of indigenous soil bacteria. On the other hand, extraction wells check the movement of plume along downstream. In this study, optimal design of the system has been done using PSO (Particle Swarm Optimization) algorithm. A comprehensive management strategy for pumping of injection and extraction wells has been done to attain a maximum allowable concentration of 5 ppm and 4.5 ppm. The management strategy comprises determination of pumping rates, the total pumping volume and the total running cost incurred for each potential injection and extraction well. The results indicate a high pumping rate for injection wells during the initial management period since it facilitates the availability of oxygen and other nutrients necessary for biodegradation, however it is low during the third year on account of sufficient oxygen availability. This is because the contaminant is assumed to have biodegraded by the end of the third year when the concentration drops to a permissible level.

Keywords: groundwater, in-situ bioremediation, light non-aqueous phase liquid, BTEX, particle swarm optimization

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Authors: Muhammad Rezal Kamel Ariffin, Muhammad Asyraf Asbullah

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The square root modulo problem is a known primitive in designing an asymmetric cryptosystem. It was first attempted by Rabin. Decryption failure of the Rabin cryptosystem caused by the 4-to-1 decryption output is overcome efficiently in this work. The proposed scheme to overcome the decryption failure issue (known as the AAβ-cryptosystem) is constructed using a simple mathematical structure, it has low computational requirements and would enable communication devices with low computing power to deploy secure communication procedures efficiently.

Keywords: Rabin cryptosystem, 4-to-1 decryption failure, square root modulo problem, integer factorization problem

Procedia PDF Downloads 475

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

Procedia PDF Downloads 338

Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

Procedia PDF Downloads 365

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a new hybrid Hopfield neural network is proposed for the dynamic, flexible job shop scheduling problem. A new heuristic based and easy to implement energy function is designed for the Hopfield neural network, which penalizes the constraints violation and decreases makespan. Moreover, for enhancing the performance, several heuristics are integrated to it that achieve active, and non-delay schedules also, prevent early convergence of the neural network. The suggested algorithm that is designed as a generalization of the previous studies for the flexible and dynamic scheduling problems can be used for solving real scheduling problems. Comparison of the presented hybrid method results with the previous studies results proves its efficiency.

Keywords: dynamic flexible job shop scheduling, neural network, heuristics, constrained optimization

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Authors: Saghar Heidari

Abstract:

In this paper, we study the valuation problem of European continuous-installment options under Markov-modulated models with a partial differential equation approach. Due to the opportunity for continuing or stopping to pay installments, the valuation problem under regime-switching models can be formulated as coupled partial differential equations (CPDE) with free boundary features. To value the installment options, we express the truncated CPDE as a linear complementarity problem (LCP), then a finite element method is proposed to solve the resulted variational inequality. Under some appropriate assumptions, we establish the stability of the method and illustrate some numerical results to examine the rate of convergence and accuracy of the proposed method for the pricing problem under the regime-switching model.

Keywords: continuous-installment option, European option, regime-switching model, finite element method

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Authors: Nileshkumar Vaishnav, Aditya Tatu

Abstract:

An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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Authors: Tamrat Tesfaye, Bruce Sithole

Abstract:

Box-Behnken Response surface methodology was used to determine the optimum processing conditions that give maximum extraction yield and whiteness index from mango seed. The steeping time ranges from 2 to 12 hours and slurring of the steeped seed in sodium metabisulphite solution (0.1 to 0.5 w/v) was carried out. Experiments were designed according to Box-Behnken Design with these three factors and a total of 15 runs experimental variables of were analyzed. At linear level, the concentration of sodium metabisulphite had significant positive influence on percentage yield and whiteness index at p<0.05. At quadratic level, sodium metabisulphite concentration and sodium metabisulphite concentration2 had a significant negative influence on starch yield; sodium metabisulphite concentration and steeping time*temperature had significant (p<0.05) positive influence on whiteness index. The adjusted R2 above 0.8 for starch yield (0.906465) and whiteness index (0.909268) showed a good fit of the model with the experimental data. The optimum sodium metabisulphite concentration, steeping hours, and temperature for starch isolation with maximum starch yield (66.428%) and whiteness index (85%) as set goals for optimization with the desirability of 0.91939 was 0.255w/v concentration, 2hrs and 50 °C respectively. The determined experimental value of each response based on optimal condition was statistically in accordance with predicted levels at p<0.05. The Mango seeds are the by-products obtained during mango processing and possess disposal problem if not handled properly. The substitution of food based sizing agents with mango seed starch can contribute as pertinent resource deployment for value-added product manufacturing and waste utilization which might play significance role of food security in Ethiopia.

Keywords: mango, synthetic sizing agent, starch, extraction, textile, sizing

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Authors: Agnese Natali, Francesco Morelli, Walter Salvatore

Abstract:

Automated Rack Supported Warehouses (ARSWs) are storage buildings whose structure is made of the same racks where goods are placed. The possibility of designing dissipative seismic-resistant ARSWs is investigated. Diagonals are the dissipative elements, arranged as tense-only X bracings. Local optimization is numerically performed to satisfy the over-resistant connection request for the dissipative element, that is hard to be reached due the geometrical limits of the thin-walled diagonals and must be balanced with resistance, the limit of slenderness, and ductility requests.

Keywords: steel racks, thin-walled cold-formed elements, structural optimization, hierarchy rules, dog-bone philosophy

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Authors: Christian Meinecke, Bernd Scholz-Reiter

Abstract:

The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve sub-problems. A heuristic using a multi-step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: production and outbound distribution, integrated planning, heuristic, decomposition, integration

Procedia PDF Downloads 429