Search results for: vision-based path optimization

Authors: Baskar Kotte

Abstract:

Many organizations are constantly striving to implement numerous techniques for long-term sustainability, for food related organizations it is imperative to conceptualize the critical concepts which constitute food safety sustainability. This presentation provides three critical pillars to develop a sustainable organization. Financial sustainability, regulatory sustainability and excellence standards sustainability are the three components which practiced and implemented effectively with process performance metrics defined objectives and targets lead to sustainable and safe food organizations. The participants take away a well-developed concept diagram with all elements impacting sustainability. Proven disciplined path which worked to achieve desired results is presented for effective implementation. Effective implementation of this proven disciplined path positions organizations to achieve world class status with bottomline improvement. Additionally, this presentation highlights critical terms, principles and implementation difficulties related to using the proven disciplined path. This presentation is beneficial for business leaders, food safety compliance managers, food safety practitioners, financial managers, Lean & Six sigma continual improvement managers, BRC/SQF/ IFS / FSSC 22000 practitioners and food manufacturing personnel.

Keywords: food safety, sustainability, regulatory, lean, six sigma, bottom-line improvement disciplined path

Procedia PDF Downloads 255

Authors: R. Furutani, G. Kikuchi

Abstract:

Generally, the optical interferometer system is too complicated and difficult to change the measurement items, pitch, yaw, and row, etc. In this article, the optical interferometer system using the transmissive Liquid Crystal Device (LCD) as the switch of the optical path was proposed. At first, the normal optical interferometer, Michelson interferometer, was constructed to measure the pitch angle and the yaw angle. In this optical interferometer, the ball lenses with the refractive indices of 2.0 were used as the retroreflectors. After that, the transmissive LCD was introduced as the switch to select the adequate optical path. In this article, these optical systems were constructed. Pitch measurement interferometer and yaw measurement interferometer were switched by the transmissive LCD. When the LCD was open for the yaw measurement, the yaw was sufficiently measured and optical path for the pitch measurement was blocked. On the other hand, when the LCD was open for the pitch measurement, the pitch was measured and the optical path for the yaw measurement was also blocked. In this article, the results of both of pitch measurement and yaw measurement were shown, and the result of blocked yaw measurement and pitch measurement were shown. As this measurement system was based on Michelson interferometer, the other measuring items, the deviation along the optical axis, the vertical deviation to the optical axis and row angle, could be measured by the additional ball lenses and the additional switching in future work.

Keywords: any direction angle, ball lens, laser interferometer, transmissive liquid crystal device

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Authors: P. Parthiban, Sonu Rajak, N. Kannan, R. Dhanalakshmi

Abstract:

This paper deals with the Vehicle Routing Problem (VRP) with environmental considerations which is called Pollution Routing Problem (PRP). The objective is to minimize the operational and environmental costs. It consists of routing a number of vehicles to serve a set of customers, and determining fuel consumption, driver wages and their speed on each route segment, while respecting the capacity constraints and time windows. In this context, we presented an Ant Colony Optimization (ACO) approach, combined with a Speed Optimization Algorithm (SOA) to solve the PRP. The proposed solution method consists of two stages. Stage one is to solve a Vehicle Routing Problem with Time Window (VRPTW) using ACO and in the second stage a SOA is run on the resulting VRPTW solutions. Given a vehicle route, the SOA consists of finding the optimal speed on each arc of the route in order to minimize an objective function comprising fuel consumption costs and driver wages. The proposed algorithm tested on benchmark problem, the preliminary results show that the proposed algorithm is able to provide good solutions.

Keywords: ant colony optimization, CO2 emissions, combinatorial optimization, speed optimization, vehicle routing

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Authors: Sang Ho Lee, Tae Heon Moon, Youn Taik Leem, Kwang Woo Nam

Abstract:

Knowledge and IT inputs to other industrial production have become more important as a key factor for the competitiveness of national and regional economies, such as knowledge economies in smart cities. Knowledge and IT industries lead the industrial innovation and technical (r)evolution through low cost, high efficiency in production, and by creating a new value chain and new production path chains, which is referred as knowledge and IT dynamics. This study aims to investigate the knowledge and IT dynamics in Korea, which are analyzed through the input-output model and structural path analysis. Twenty-eight industries were reclassified into seven categories; Agriculture and Mining, IT manufacture, Non-IT manufacture, Construction, IT-service, Knowledge service, Non-knowledge service to take close look at the knowledge and IT dynamics. Knowledge and IT dynamics were analyzed through the change of input output coefficient and multiplier indices in terms of technical innovation, as well as the changes of the structural paths of the knowledge and IT to other industries in terms of new production value creation from 1985 and 2010. The structural paths of knowledge and IT explain not only that IT foster the generation, circulation and use of knowledge through IT industries and IT-based service, but also that knowledge encourages IT use through creating, sharing and managing knowledge. As a result, this paper found the empirical investigation on the knowledge and IT dynamics of the Korean economy. Knowledge and IT has played an important role regarding the inter-industrial transactional input for production, as well as new industrial creation. The birth of the input-output production path has mostly originated from the knowledge and IT industries, while the death of the input-output production path took place in the traditional industries from 1985 and 2010. The Korean economy has been in transition to a knowledge economy in the Smart City.

Keywords: knowledge and IT industries, input-output model, structural path analysis, dynamics of knowledge and it, knowledge economy, knowledge city and smart city

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Authors: Harald Lang, Michael Bader, A. Buchroithner

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Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: design, product development, product optimization, systems engineering

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Authors: Willian C. De Brito, Hernan D. C. Munoz, Erlan V. C. Carvalho, Helder L. C. De Oliveira

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In order to improve commute time for small distance trips and relieve large cities traffic, a new transport category has been the subject of research and new designs worldwide. The air taxi travel market promises to change the way people live and commute by using the concept of vehicles with the ability to take-off and land vertically and to provide passenger’s transport equivalent to a car, with mobility within large cities and between cities. Today’s civil air transport remains costly and accounts for 2% of the man-made CO₂ emissions. Taking advantage of this scenario, many companies have developed their own Vertical Take Off and Landing (VTOL) design, seeking to meet comfort, safety, low cost and flight time requirements in a sustainable way. Thus, the use of green power supplies, especially batteries, and fully electric power plants is the most common choice for these arising aircrafts. However, it is still a challenge finding a feasible way to handle with the use of batteries rather than conventional petroleum-based fuels. The batteries are heavy and have an energy density still below from those of gasoline, diesel or kerosene. Therefore, despite all the clear advantages, all electric aircrafts (AEA) still have low flight autonomy and high operational cost, since the batteries must be recharged or replaced. In this sense, this paper addresses a way to optimize the energy consumption in a typical mission of an aerial taxi aircraft. The approach and landing procedure was chosen to be the subject of an optimization genetic algorithm, while final programming can be adapted for take-off and flight level changes as well. A real tilt rotor aircraft with fully electric power plant data was used to fit the derived dynamic equations of motion. Although a tilt rotor design is used as a proof of concept, it is possible to change the optimization to be applied for other design concepts, even those with independent motors for hover and cruise flight phases. For a given trajectory, the best set of control variables are calculated to provide the time history response for aircraft´s attitude, rotors RPM and thrust direction (or vertical and horizontal thrust, for independent motors designs) that, if followed, results in the minimum electric power consumption through that landing path. Safety, comfort and design constraints are assumed to give representativeness to the solution. Results are highly dependent on these constraints. For the tested cases, performance improvement ranged from 5 to 10% changing initial airspeed, altitude, flight path angle, and attitude.

Keywords: air taxi travel, all electric aircraft, batteries, energy consumption, genetic algorithm, landing performance, optimization, performance improvement, tilt rotor, VTOL design

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

Abstract:

This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: M. Dezvarei, S. Morovati

Abstract:

In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: Khaled M. El Naggar

Abstract:

This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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Authors: Elham Kiyani, S. Mansour Vaezpour, Javad Tavakoli

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In this paper, we first introduce a new distance function in a linear space not necessarily endowed with a topology. The algebraic concepts of interior and closure are useful to study optimization problems without topology. So, we define Q-weak efficient solutions generated by the algebraic interior of a set Q, where Q is not necessarily convex. Studying nonconvex vector optimization is valuable since, for a convex cone K in topological spaces, we have int(K)=cor(K), which means that topological interior of a convex cone K is equal to the algebraic interior of K. Moreover, we used the scalarization technique including the distance function generated by the vectorial closure of a set to characterize these Q-weak efficient solutions. Scalarization is a useful approach for solving vector optimization problems. This technique reduces the optimization problem to a scalar problem which tends to be an optimization problem with a real-valued objective function. For instance, Q-weak efficient solutions of vector optimization problems can be characterized and computed as solutions of appropriate scalar optimization problems. In the convex case, linear functionals can be used as objective functionals of the scalar problems. But in the nonconvex case, we should present a suitable objective function. It is the aim of this paper to present a new distance function that be useful to obtain sufficient and necessary conditions for Q-weak efficient solutions of general optimization problems via scalarization.

Keywords: weak efficient, algebraic interior, vector closure, linear space

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Samia Sadouki Chibani, Abdelkamel Tari

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Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: bio-inspired algorithms, elephant herding optimization, QoS optimization, web service composition

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Authors: Benmoussa Dennai, H. Benslimane, A. Helmaoui

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Photo voltaic conversion is the direct conversion of electromagnetic energy into electrical energy continuously. This electromagnetic energy is the most solar radiation. In this work we performed a computer modelling using AMPS 1D optimization of hetero-junction solar cells GaInP/GaAs configuration for p/ n. We studied the influence of the thickness the base layer in the cell offers on the open circuit voltage, the short circuit current and efficiency.

Keywords: optimization, photovoltaic cell, GaInP / GaAs AMPS-1D, hetetro-junction

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

Abstract:

Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

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This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

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Authors: Baoshan Wei, Shuai Han, Xing Zhang

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Local obstacle avoidance is critical for mobile robot navigation. It is a challenging task to ensure path optimality and safety in cluttered environments. We proposed an Environment Aware Dynamic Window Approach in this paper to cope with the issue. The method integrates environment characterization into Dynamic Window Approach (DWA). Two strategies are proposed in order to achieve the integration. The local goal strategy guides the robot to move through openings before approaching the final goal, which solves the local minima problem in DWA. The adaptive control strategy endows the robot to adjust its state according to the environment, which addresses path safety compared with DWA. Besides, the evaluation shows that the path generated from the proposed algorithm is safer and smoother compared with state-of-the-art algorithms.

Keywords: adaptive control, dynamic window approach, environment aware, local obstacle avoidance, mobile robots

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Authors: Mohammad Reza Ramezani, Shahriyar Afandizadeh

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Since the intersections play a crucial role in traffic delay, it is significant to evaluate them precisely. In this paper, three critical intersections in Tehran (Capital of Iran) had been simulated. The main purpose of this paper was to optimize the public transit delay. The simulation had three different phase in three intersections of Tehran. The first phase was about the current condition of intersection; the second phase was about optimized signal timing and the last phase was about prioritized public transit access. The Aimsun software was used to simulate all phases, and the Synchro software was used to optimization of signals as well. The result showed that the implement of optimization and prioritizing system would reduce about 50% of delay for public transit.

Keywords: transit signal priority, intersection optimization, public transit, simulation

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Authors: Ju-Hong Lee, Ding-Chen Chung

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This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto

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In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.

Keywords: odor sensor, odor source localization, optimization, sensor network

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Authors: Ahmed Cherif Megri, HossamEldin ElSherif

Abstract:

In a power plant, the header pipe plays a pivotal role in optimizing the performance of diverse systems by serving as a central conduit for the collection and distribution of steam within the plant. This paper investigates the significance of header pipes within power plant setups, highlighting their critical influence on reliability, efficiency, and the performance of the power plant as a whole. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint of power plant installations. In this paper, we initially developed a methodology designed for optimizing header shapes with the primary goal of reducing the usage of costly new alloy materials and lowering the overall maintenance operation expenses. Secondly, we conducted a case study based on an authentic header sourced from an operational power plant.

Keywords: shape optimization, header, power plant, inconel alloy, CFD, structural optimization

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Authors: Faisel Elramalli, Ibrahim Althomali Amjad Sabbagh, Dhananjay Tambe

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SPEC CPU benchmarks are used to evaluate the performance of CPUs on computer systems. In our project we are going to use SPEC CPU suite that contains several benchmarks running on two different compilers gcc and icc in different optimizations levels to evaluate the performance of a CPU. The motivation of this project is to find out which compiler and in which optimization level makes the CPU reaches the best performance. The results of that evaluation will help users of these compilers to choose the best compiler and optimization level that perform efficiently for their work. In other words, it will give users the best performance of the CPU while doing their works. This project is interesting since it will provide the method used to measure the performance of CPU and how different optimization levels of compilers can help achieve a higher performance. Moreover, it will give a good understanding of how benchmarks are used to evaluate a CPU performance. For the reader, in reality SPEC CPU benchmarks are used to measure the performance of new released CPUs to be compared to other CPUs.

Keywords: SPEC, CPU, GCC, ICC, copilers

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Authors: Ali Dorostkar

Abstract:

In this paper, a basic schematic of fractional dimensional optimization problem is presented. As will be shown, a method is performed based on a relation between roots and tangent lines of function in fractional dimensions for an arbitrary initial point. It is shown that for each polynomial function with order N at least N tangent lines must be existed in fractional dimensions of 0 < α < N+1 which pass exactly through the all roots of the proposed function. Geometrical analysis of tangent lines in fractional dimensions is also presented to clarify more intuitively the proposed method. Results show that with an appropriate selection of fractional dimensions, we can directly find the roots. Method is presented for giving a different direction of optimization problems by the use of fractional dimensions.

Keywords: tangent line, fractional dimension, root, optimization problem

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Authors: Seyedmahdi Mousavihashemi

Abstract:

One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

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Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

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This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

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Authors: Ersin Sener, Ibrahim Demir, Hasan Aykut Karaboga, Kadir Kilinc

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Bayesian methods, which have very wide range of applications, are implemented to the data obtained from the production of F class fly ash-based geopolymer bricks’ experimental design. In this study, dependent variable is compressive strength, independent variables are treatment type (oven and steam), treatment time, molding time, temperature, water absorbtion ratio and density. The effect of independent variables on compressive strength is investigated. There is no difference among treatment types, but there is a correlation between independent variables. Therefore, hierarchical Bayesian path analysis is applied. In consequence of analysis we specified that treatment time, temperature and density effects on compressive strength is higher, molding time, and water absorbtion ratio is relatively low.

Keywords: experimental design, F class fly ash, geopolymer bricks, hierarchical Bayesian path analysis

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Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Benmoussa Dennai, H. Benslimane, A. Helmaoui

Abstract:

Photovoltaic conversion is the direct conversion of electromagnetic energy into electrical energy continuously. This electromagnetic energy is the most solar radiation. In this work we performed a computer modelling using AMPS 1D optimization of hetero-junction solar cells GaInP / GaAs configuration for p / n. We studied the influence of the thickness the base layer in the cell offers on the open circuit voltage, the short circuit current and efficiency.

Keywords: optimization, photovoltaic cell, GaInP / GaAs AMPS-1D, hetetro-junction

Procedia PDF Downloads 491