Search results for: complex optimization method

Authors: R. Rama Kishore, Sunesh

Abstract:

Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

Procedia PDF Downloads 350

Authors: Y. L. Hor, H. S. Chu, V. P. Bui

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Composite material is widely used to replace conventional material, especially in the aerospace industry to reduce the weight of the devices. It is formed by combining reinforced materials together via adhesive bonding to produce a bulk material with alternated macroscopic properties. In bulk composites, degradation may occur in microscopic scale, which is in each individual reinforced fiber layer or especially in its matrix layer such as delamination, inclusion, disbond, void, cracks, and porosity. In this paper, we focus on the detection of defect in matrix layer which the adhesion between the composite plies is in contact but coupled through a weak bond. In fact, the adhesive defects are tested through various nondestructive methods. Among them, pulsed phase thermography (PPT) has shown some advantages providing improved sensitivity, large-area coverage, and high-speed testing. The aim of this work is to develop an efficient numerical model to study the application of PPT to the nondestructive inspection of weak bonding in composite material. The resulting thermal evolution field is comprised of internal reflections between the interfaces of defects and the specimen, and the important key-features of the defects presented in the material can be obtained from the investigation of the thermal evolution of the field distribution. Computational simulation of such inspections has allowed the improvement of the techniques to apply in various inspections, such as materials with high thermal conductivity and more complex structures.

Keywords: pulsed phase thermography, weak bond, composite, CFRP, computational modelling, optimization

Procedia PDF Downloads 155

Authors: Prateek Singh, Dilshad Ahmad

Abstract:

Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.

Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish

Procedia PDF Downloads 192

Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

Procedia PDF Downloads 805

Authors: Carine Muster, Prina Howald Erika

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Today's ice rinks are important energy consumers for the production and maintenance of ice. At the same time, users demand that the other rooms should be tempered or heated. The building complex must equally provide cooled and heated zones, which does not translate as carbon-zero ice rinks. The study provides an analysis of how the civil engineering sector can significantly impact minimizing greenhouse gas emissions and optimizing synergies across an entire ice rink complex. The analysis focused on three distinct aspects: the layout, including the volumetric layout of the premises present in an ice rink; the materials chosen that can potentially use the most ecological structural approach; and the construction methods based on innovative solutions to reduce carbon footprint. The first aspect shows that the organization of the interior volumes and defining the shape of the rink play a significant role. Its layout makes the use and operation of the premises as efficient as possible, thanks to the differentiation between heated and cooled volumes while optimising heat loss between the different rooms. The sprayed concrete method, which is still little known, proves that it is possible to achieve the strength of traditional concrete for the structural aspect of the load-bearing and non-load-bearing walls of the ice rink by using materials excavated from the construction site and providing a more ecological and sustainable solution. The installation of an empty sanitary space underneath the ice floor, making it independent of the rest of the structure, provides a natural insulating layer, preventing the transfer of cold to the rest of the structure and reducing energy losses. The addition of active pipes as part of the foundation of the ice floor, coupled with a suitable system, gives warmth in the winter and storage in the summer; this is all possible thanks to the natural heat in the ground. In conclusion, this study provides construction recommendations for future ice rinks with a significantly reduced energy demand, using some simple preliminary design concepts. By optimizing the layout, materials, and construction methods of ice rinks, the civil engineering sector can play a key role in reducing greenhouse gas emissions and promoting sustainability.

Keywords: climate change, energy optimization, green building, sustainability

Procedia PDF Downloads 51

Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

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Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

Procedia PDF Downloads 504

Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Rusli Othman

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This paper presents the surface roughness of the aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN). Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to a standard orthogonal array L27 of Taguchi method using TiN coating tool of insert. The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of cutting speeds, feed rates and depths of cut in measuring the surface roughness during the milling operation. The surface roughness was observed using Mitutoyo Formtracer CS-500 and analyzed using the Taguchi method. From the Taguchi analysis, it was found that cutting speed of 230 m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.3 mm were the optimum machining parameters using TiN coating insert.

Keywords: AlSi/AlN metal matrix composite (MMC), surface roughness, Taguchi method, machining parameters

Procedia PDF Downloads 418

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

Procedia PDF Downloads 284

Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

Procedia PDF Downloads 475

Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Thomas Doutre, Emmanuel De Meric De Bellefon

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This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling.

Keywords: optimization, portfolio risk management, quantum annealing, metaheuristic

Procedia PDF Downloads 368

Authors: Niranjana Devi N.

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Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

Procedia PDF Downloads 652

Authors: Mondher Yahyaoui

Abstract:

A generalized vortex lattice method for complex lifting surfaces with flap and aileron deflection is formulated. The method is not restricted by the linearized theory assumption and accounts for all standard geometric lifting surface parameters: camber, taper, sweep, washout, dihedral, in addition to flap and aileron deflection. Thickness is not accounted for since the physical lifting body is replaced by a lattice of panels located on the mean camber surface. This panel lattice setup and the treatment of different wake geometries is what distinguish the present work form the overwhelming majority of previous solutions based on the vortex lattice method. A MATLAB code implementing the proposed formulation is developed and validated by comparing our results to existing experimental and numerical ones and good agreement is demonstrated. It is then used to study the accuracy of the widely used classical vortex-lattice method. It is shown that the classical approach gives good agreement in the clean configuration but is off by as much as 30% when a flap or aileron deflection of 30° is imposed. This discrepancy is mainly due the linearized theory assumption associated with the conventional method. A comparison of the effect of four different wake geometries on the values of aerodynamic coefficients was also carried out and it is found that the choice of the wake shape had very little effect on the results.

Keywords: aileron deflection, camber-surface-bound vortices, classical VLM, generalized VLM, flap deflection

Procedia PDF Downloads 425

Authors: I. O. Nascimento, J. T. Manzi

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The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.

Keywords: thermodynamic optimization, drying, entropy minimization, modeling dryers

Procedia PDF Downloads 250

Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

Procedia PDF Downloads 379

Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

Procedia PDF Downloads 230

Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all the mechanical properties of fibers, matrix, the fiber/matrix interface, as well as the geometry of the fiber. An appropriate method applicable to the simulation and analysis of toughening is essential. In this work, we performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of the contribution of random fibers to the toughening of composite. Then with numerical programming, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers with high strength and low elasticity modulus benefit toughening; (ii) fibers with relatively high elastic modulus compared to the matrix may result in considerable matrix damage (spalling effect); (iii) employment of high-strength synthetic fiber is a good option. The present work makes it possible to optimize the parameters in order to produce advanced ceramic with desired performance. We believe combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed.

Keywords: bridging stress, discrete element method, fiber reinforced composites, toughening

Procedia PDF Downloads 433

Authors: Mohammadreza Akbari, Sara Akbari, Davood Domiri Ganji, Pooya Solimani, Reza Khalili

Abstract:

As all experts know most of engineering system behavior in practical are nonlinear process (especially heat, fluid and mass, etc.) and analytical solving (no numeric) these problems are difficult, complex and sometimes impossible like (fluids and gas wave, these problems can't solve with numeric method, because of no have boundary condition) accordingly in this symposium we are going to exposure a innovative approach which we have named it Akbari-Ganji's Method or AGM in engineering, that can solve sets of coupled nonlinear differential equations (ODE, PDE) with high accuracy and simple solution and so this issue will be emerged after comparing the achieved solutions by Numerical method (Runge-Kutte 4th) and so compare to other methods such as HPM, ADM,… and exact solutions. Eventually, AGM method will be proved that could be created huge evolution for researchers, professors and students (engineering and basic science) in whole over the world, because of AGM coding system, so by using this software we can analytically solve all complicated linear and nonlinear differential equations, with help of that there is no difficulty for solving nonlinear differential equations(ODE and PDE). In this paper, we investigate and solve 4 types of the nonlinear differential equation with AGM method : 1-Heat and fluid, 2-Unsteady state of nonlinear partial differential, 3-Coupled nonlinear partial differential in wave equation, and 4-Nonlinear integro-differential equation.

Keywords: new method AGM, sets of coupled nonlinear equations at engineering field, waves equations, integro-differential, fluid and thermal

Procedia PDF Downloads 531

Authors: Guanglin Song

Abstract:

(Objective) Situated within the context of China's tiered medical treatment system, this study aims to analyze spatial causes of urban healthcare access difficulties from the perspective of the configuration of healthcare facilities. (Methods) A social network analysis approach is employed to construct a healthcare demand and supply flow network between major residential clusters and various tiers of hospitals in the city.(Conclusion) The findings reveal that:1.there exists overall maldistribution and over-concentration of healthcare resources in Study Area, characterized by structural imbalance; 2.the low rate of primary care utilization in Study Area is a key factor contributing to congestion at higher-tier hospitals, as excessive reliance on these institutions by neighboring communities exacerbates the problem; 3.gradual optimization of the healthcare facility layout in Study Area, encompassing holistic, local, and individual institutional levels, can enhance systemic efficiency and resource balance.(Prospects) This research proposes a method for evaluating urban healthcare resource distribution structures based on service flows within hierarchical networks. It offers spatially targeted optimization suggestions for promoting the implementation of the tiered healthcare system and alleviating challenges related to accessibility and congestion in seeking medical care. Provide some new ideas for researchers and healthcare managers in countries, cities, and healthcare management around the world with similar challenges.

Keywords: flow of public services, urban networks, healthcare facilities, spatial planning, urban networks

Procedia PDF Downloads 47

Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

Procedia PDF Downloads 52

Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

Procedia PDF Downloads 255

Authors: Atefeh Esmailnejad, Gholamreza Nikbakht Brujeni

Abstract:

Major histocompatibility complex (MHC) is one of the best characterized genetic regions associated with immune responses and controlling disease resistance in chicken. Association of the MHC with a wide range of immune responses makes it a valuable predictive factor for the disease pathogenesis and outcome. In this study, the association of MHC with cell-mediated immune responses was analyzed in commercial broiler chicken. The tandem repeat LEI0258 was applied to investigate the MHC polymorphism. Cell-mediated immune response was evaluated by peripheral blood lymphocyte proliferation assay using MTT method. Association study revealed a significant influence of MHC alleles on cellular immune responses in this population. Alleles 385 and 448 bp were associated with elevated cell-mediated immunity. Haplotypes associated with improved immune responses could be considered as candidate markers for disease resistance and applied to breeding strategies.

Keywords: MHC, cell-mediated immunity, broiler, chicken

Procedia PDF Downloads 136

Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

Abstract:

Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

Procedia PDF Downloads 98

Authors: A. A. Behroozpoor, M. M. Mazarei

Abstract:

In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

Procedia PDF Downloads 629

Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza Khalili, Sara Akbari

Abstract:

In this study, we investigate building structures nonlinear behavior also solving analytic of nonlinear differential at vibrations. As we know most of engineering systems behavior in practical are non- linear process (especial at structural) and analytical solving (no numerical) these problems are complex, difficult and sometimes impossible (of course at form of analytical solving). In this symposium, we are going to exposure one method in engineering, that can solve sets of nonlinear differential equations with high accuracy and simple solution and so this issue will emerge after comparing the achieved solutions by Numerical Method (Runge-Kutte 4th) and exact solutions. Finally, we can proof AGM method could be created huge evolution for researcher and student (engineering and basic science) in whole over the world, because of AGM coding system, so by using this software, we can analytical solve all complicated linear and nonlinear differential equations, with help of that there is no difficulty for solving nonlinear differential equations.

Keywords: new method AGM, vibrations, beam-column, angular frequency, energy dissipated, critical load

Procedia PDF Downloads 373

Authors: L. Heidari, M. Jalili Ghazizade

Abstract:

In recent years, different petrochemical complexes have been established to produce aromatic compounds. Among them, Nouri Petrochemical Complex (NPC) is the largest producer of aromatic raw materials in the world, and is located in south of Iran. Environmental concerns have been raised in this region due to generation of different types of solid waste generated in the process of aromatics production, and subsequently, industrial waste characterization has been thoroughly considered. The aim of this study is qualitative and quantitative characterization of industrial waste generated in the aromatics production process and determination of the best method for industrial waste management. For this purpose, all generated industrial waste during the production process was determined using a checklist. Four main industrial wastes were identified as follows: spent industrial soil, spent catalyst, spent molecular sieves and spent N-formyl morpholine (NFM) solvent. The amount of heavy metals and organic compounds in these wastes were further measured in order to identify the nature and toxicity of such a dangerous compound. Then industrial wastes were classified based on lab analysis results as well as using different international lists of hazardous waste identification such as EPA, UNEP and Basel Convention. Finally, the best method of waste disposal is selected based on environmental, economic and technical aspects. 

Keywords: aromatic compounds, industrial soil, molecular sieve, normal formyl morpholine solvent

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

Abstract:

Apparent quality defects such as warpage, shrinkage, weld line, etc. are such an irresistible phenomenon in mass production of auto plastic appearance parts. These frequently occurred manufacturing defects should be satisfied concurrently so as to achieve a final product with acceptable quality standards. Determining the significant control factors that simultaneously affect multiple quality characteristics can significantly improve the optimization results by eliminating the deviating effect of the so-called ineffective outliers. Hence, a robust quantitative approach needs to be developed upon which major control factors and their level can be effectively determined to help improve the reliability of the optimal processing parameter design. Hence, the primary objective of current study was to develop a systematic methodology for selection of significant control factors (SCF) relevant to multiple quality optimization of auto plastic appearance part. Auto bumper was used as a specimen with the most identical quality and production characteristics to APAP group. A preliminary failure modes and effect analysis (FMEA) was conducted to nominate a database of pseudo significant significant control factors prior to the optimization phase. Later, CAE simulation Moldflow analysis was implemented to manipulate four rampant plastic injection quality defects concerned with APAP group including warpage deflection, volumetric shrinkage, sink mark and weld line. Furthermore, a step-backward elimination searching method (SESME) has been developed for systematic pre-optimization selection of SCF based on hierarchical orthogonal array design and priority-based one-way analysis of variance (ANOVA). The development of robust parameter design in the second phase was based on DOE module powered by Minitab v.16 statistical software. Based on the F-test (F 0.05, 2, 14) one-way ANOVA results, it was concluded that for warpage deflection, material mixture percentage was the most significant control factor yielding a 58.34% of contribution while for the other three quality defects, melt temperature was the most significant control factor with a 25.32%, 84.25%, and 34.57% contribution for sin mark, shrinkage and weld line strength control. Also, the results on the he least significant control factors meaningfully revealed injection fill time as the least significant factor for both warpage and sink mark with respective 1.69% and 6.12% contribution. On the other hand, for shrinkage and weld line defects, the least significant control factors were holding pressure and mold temperature with a 0.23% and 4.05% overall contribution accordingly.

Keywords: plastic injection moulding, quality optimization, FMEA, ANOVA, SESME, APAP

Procedia PDF Downloads 336

Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

Abstract:

It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Olga S. Volodko, Lidiya A. Kompaniets, Ludmila V. Gavrilova

Abstract:

The method of empirical orthogonal functions is the method of data analysis with a complex spatial-temporal structure. This method allows us to decompose the data into a finite number of modes determined by empirically finding the eigenfunctions of data correlation matrix. The modes have different scales and can be associated with various physical processes. The empirical orthogonal function method has been widely used for the analysis of hydrophysical characteristics, for example, the analysis of sea surface temperatures in the Western North Atlantic, ocean surface currents in the North Carolina, the study of tropical wave disturbances etc. The method used in this study has been applied to the analysis of temperature and velocity measurements in saline Lake Shira (Southern Siberia, Russia). Shira is a shallow lake with the maximum depth of 25 m. The lake Shira can be considered as a closed water site because of it has one small river providing inflow and but it has no outflows. The main factor that causes the motion of fluid is variable wind flows. In summer the lake is strongly stratified by temperature and saline. Long-term measurements of the temperatures and currents were conducted at several points during summer 2014-2015. The temperature has been measured with an accuracy of 0.1 ºC. The data were analyzed using the empirical orthogonal function method in the real version. The first empirical eigenmode accounts for 70-80 % of the energy and can be interpreted as temperature distribution with a thermocline. A thermocline is a thermal layer where the temperature decreases rapidly from the mixed upper layer of the lake to much colder deep water. The higher order modes can be interpreted as oscillations induced by internal waves. The currents measurements were recorded using Acoustic Doppler Current Profilers 600 kHz and 1200 kHz. The data were analyzed using the empirical orthogonal function method in the complex version. The first empirical eigenmode accounts for about 40 % of the energy and corresponds to the Ekman spiral occurring in the case of a stationary homogeneous fluid. Other modes describe the effects associated with the stratification of fluids. The second and next empirical eigenmodes were associated with dynamical modes. These modes were obtained for a simplified model of inhomogeneous three-level fluid at a water site with a flat bottom.

Keywords: Ekman spiral, empirical orthogonal functions, data analysis, stratified fluid, thermocline

Procedia PDF Downloads 124