Search results for: optimization and simulation.

Authors: F. Alwafie

Abstract:

In this paper, we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave.

The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wideband characteristics of the channel: root mean square (RMS) delay spread characteristics and Mean excess delay, is also investigated.

Keywords: Propagation, Ray Tracing.

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Authors: Ran Zhao, Zhi-liang Dong, You-yuan Wang, Lin-wang Su

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In order to study pressed pile test and ultimate bearing capacity character of large-diameter steel pipe pile, based on two high-piled wharfs of Zhanjiang Port, pressed pile test and numerical simulation of three large-diameter steel pipe piles are analyzed in this paper. Anchored pile method is used to pressed pile test, and the curves of Q-s and ultimate bearing capacity are attained. Then the three piles are numerically simulated by ABAQUS, and results of numerical simulation and those of field test are comparatively analyzed. The results show that settlement value of numerical simulation is larger than that of field test in the process of loading, the difference value is widening with the increasing of load, and the ultimate difference value of settlement is 20% to 30%.

Keywords: Large-diameter steel pipe pile, field test, finite element analysis, comparative analysis.

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Authors: Sahil Sharma, Mukesh Gupta, Raj Kumar, N. S Bindra

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This paper presents an experimental investigation on the optimization and the effect of the cutting parameters on Material Removal Rate (MRR) in Plasma Arc Cutting (PAC) of EN-45A Material using Taguchi L ₁₆ orthogonal array method. Four process variables viz. cutting speed, current, stand-off-distance and plasma gas pressure have been considered for this experimental work. Analysis of variance (ANOVA) has been performed to get the percentage contribution of each process parameter for the response variable i.e. MRR. Based on ANOVA, it has been observed that the cutting speed, current and the plasma gas pressure are the major influencing factors that affect the response variable. Confirmation test based on optimal setting shows the better agreement with the predicted values.

Keywords: Analysis of variance, Material removal rate, plasma arc cutting, Taguchi method.

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Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani

Abstract:

Solar energy systems using various storages are required to be evaluated based on energy requirements and applications. Also, modeling and analysis of storage systems are necessary to increase the effectiveness of combinations of these systems. In this paper, analysis based on the MATLAB software has been analyzed to evaluate the response of the hybrid energy system considering various technologies of renewable energy and energy storage. In the present study, three different simulation scenarios are presented. Simulation output results using software for the first scenario show that the battery is effective in smoothing the overall power demand to the consumer studied during a day, but temporary loads on the grid with high frequencies, effectively cannot be canceled due to the limited response speed of battery control. Simulation outputs for the second scenario using the energy storage system show that sudden changes in demand power are paved by super saving. The majority of these sudden changes in power demand are caused by sewing consumers and receiving variable solar power (due to clouds passing through the solar array). Simulation outputs for the third scenario show the effects of the hybrid system for the same consumer and the output of the solar array, leading to the smallest amount of power demand fed into the grid, as well as demand at peak times. According to the "battery only" scenario, the displacement technique of the peak load has been significantly reduced.

Keywords: Storage system, super storage, standalone, microgrid.

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Authors: Mamoun Sqali, Mohamed Wassim Trojet

Abstract:

The requirements analysis, modeling, and simulation have consistently been one of the main challenges during the development of complex systems. The scenarios and the state machines are two successful models to describe the behavior of an interactive system. The scenarios represent examples of system execution in the form of sequences of messages exchanged between objects and are a partial view of the system. In contrast, state machines can represent the overall system behavior. The automation of processing scenarios in the state machines provide some answers to various problems such as system behavior validation and scenarios consistency checking. In this paper, we propose a method for translating scenarios in state machines represented by Discreet EVent Specification and procedure to detect implied scenarios. Each induced DEVS model represents the behavior of an object of the system. The global system behavior is described by coupling the atomic DEVS models and validated through simulation. We improve the validation process with integrating formal methods to eliminate logical inconsistencies in the global model. For that end, we use the Z notation.

Keywords: Scenarios, DEVS, synthesis, validation and verification, simulation, formal verification, z notation.

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: Dynamic area requirements, facility layout problem, optimization model, product assembly.

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Authors: Chin S. Y., Radzi, S. N. R., Maharon, I. H., Shafawi, M. A.

Abstract:

A kinetic model for propane dehydrogenation in an industrial moving bed reactor is developed based on the reported reaction scheme. The kinetic parameters and activity constant are fine tuned with several sets of balanced plant data. Plant data at different operating conditions is applied to validate the model and the results show a good agreement between the model predictions and plant observations in terms of the amount of main product, propylene produced. The simulation analysis of key variables such as inlet temperature of each reactor (Tinrx) and hydrogen to total hydrocarbon ratio (H2/THC) affecting process performance is performed to identify the operating condition to maximize the production of propylene. Within the range of operating conditions applied in the present studies, the operating condition to maximize the propylene production at the same weighted average inlet temperature (WAIT) is ΔTinrx1= -2, ΔTinrx2= +1, ΔTinrx3= +1 , ΔTinrx4= +2 and ΔH2/THC= -0.02. Under this condition, the surplus propylene produced is 7.07 tons/day as compared with base case.

Keywords: kinetic model, dehydrogenation, simulation, modeling, propane

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Authors: Hansoo Kim, Seunghak Shin

Abstract:

The differential column shortening in tall buildings can be reduced by improving material and structural characteristics of the structural systems. This paper proposes structural methods to reduce differential column shortening in reinforced concrete tall buildings; connecting columns with rigidly jointed horizontal members, using outriggers, and placing additional reinforcement at the columns. The rigidly connected horizontal members including outriggers reduce the differential shortening between adjacent vertical members. The axial stiffness of columns with greater shortening can be effectively increased by placing additional reinforcement at the columns, thus the differential column shortening can be reduced in the design stage. The optimum distribution of additional reinforcement can be determined by applying a gradient based optimization technique.

Keywords: Column shortening, long-term behavior, optimization, tall building.

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: Time Utility Function/ Utility Accrual (TUF/UA) scheduling, Real-time system (RTS), Backward Recovery, Multiprocessor, Discrete Event Simulation (DES).

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Authors: Andreas Ahrens, Ojaras Purvinis Jelena Zāšcerinska

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A successful shopping experience without overcrowded shops and long waiting times undoubtedly leads to the release of happiness hormones and is generally considered as the goal of any optimization. Factors influencing the shopping experience can be divided into internal and external ones. External factors are related e. g. to the arrival of the customers to the shop whereas internal factors are linked with the service process itself when checking out (waiting in the queue to the cash register and the scanning of the goods as well as the payment process itself) or any other non-expected delay when changing the status from a visitor to a buyer by choosing goods or items. This paper divides the customer-server interaction in five phases starting with the customer arrival at the shop, the selection of goods, the buyer waiting in the queue to the cash register, the payment process and ending with the customer or buyer departure. Our simulation results show how five phases are intertwined and influence the overall shopping experience. Parameters for measuring the shopping experience based on a burstiness level in each of the five phases of the customer-server interaction are estimated.

Keywords: Customers’ burstiness, cash register, customers’ waiting time, gap distribution function.

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Authors: S. Padmapriya, M. Tamilarasi

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Femtocells are regarded as a milestone for next generation cellular networks. As femtocells are deployed in an unplanned manner, there is a chance of assigning same resource to neighboring femtocells. This scenario may induce co-channel interference and may seriously affect the service quality of neighboring femtocells. In addition, the dominant transmit power of a femtocell will induce co-tier interference to neighboring femtocells. Thus to jointly handle co-tier and co-channel interference, we propose an interference-free power and resource block allocation (IFPRBA) algorithm for closely located, closed access femtocells. Based on neighboring list, inter-femto-base station distance and uplink noise power, the IFPRBA algorithm assigns non-interfering power and resource to femtocells. The IFPRBA algorithm also guarantees the quality of service to femtouser based on the knowledge of resource requirement, connection type, and the tolerable delay budget. Simulation result shows that the interference power experienced in IFPRBA algorithm is below the tolerable interference power and hence the overall service success ratio, PRB efficiency and network throughput are maximum when compared to conventional resource allocation framework for femtocell (RAFF) algorithm.

Keywords: Co-channel interference, co-tier interference, femtocells, guaranteed QoS, power optimization, resource assignment.

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Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: Magnetic Resonance Image, C-means model, image segmentation, information entropy.

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: Watershed simulation, WetSpa, stream flow, flood prediction.

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Authors: Ayed Salman, Fawaz Al-Anzi, Aseel Al-Minayes

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Heuristics-based search methodologies normally work on searching a problem space of possible solutions toward finding a “satisfactory" solution based on “hints" estimated from the problem-specific knowledge. Research communities use different types of methodologies. Unfortunately, most of the times, these hints are immature and can lead toward hindering these methodologies by a premature convergence. This is due to a decrease of diversity in search space that leads to a total implosion and ultimately fitness stagnation of the population. In this paper, a novel Decision Maturity framework (DMF) is introduced as a solution to this problem. The framework simply improves the decision on the direction of the search by materializing hints enough before using them. Ideas from this framework are injected into the particle swarm optimization methodology. Results were obtained under both static and dynamic environment. The results show that decision maturity prevents premature converges to a high degree.

Keywords: Heuristic Search, hints, Particle Swarm Optimization, Decision Maturity Framework.

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Authors: Latifeh PourMohammadBagher

Abstract:

In this paper I have developed a system for evaluating the degree of fear emotion that the intelligent agent-based system may feel when it encounters to a persecuting event. In this paper I want to describe behaviors of emotional agents using human behavior in terms of the way their emotional states evolve over time. I have implemented a fuzzy inference system using Java environment. As the inputs of this system, I have considered three parameters related on human fear emotion. The system outputs can be used in agent decision making process or choosing a person for team working systems by combination the intensity of fear to other emotion intensities.

Keywords: Emotion simulation, Fear, Fuzzy intelligent agent

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Authors: Jieh-Haur Chen, Pei-Fen Huang

Abstract:

This paper presents an integrated model that automatically measures the change of rivers, damage area of bridge surroundings, and change of vegetation. The proposed model is on the basis of a neurofuzzy mechanism enhanced by SOM optimization algorithm, and also includes three functions to deal with river imagery. High resolution imagery from FORMOSAT-2 satellite taken before and after the invasion period is adopted. By randomly selecting a bridge out of 129 destroyed bridges, the recognition results show that the average width has increased 66%. The ruined segment of the bridge is located exactly at the most scour region. The vegetation coverage has also reduced to nearly 90% of the original. The results yielded from the proposed model demonstrate a pinpoint accuracy rate at 99.94%. This study brings up a successful tool not only for large-scale damage assessment but for precise measurement to disasters.

Keywords: remote sensing image, damage assessment, typhoon disaster, bridge, ANN, fuzzy, SOM, optimization.

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Authors: T. Balogh, L. G. Vigh

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Seismic design may require non-conventional concept, due to the fact that the stiffness and layout of the structure have a great effect on the overall structural behaviour, on the seismic load intensity as well as on the internal force distribution. To find an economical and optimal structural configuration the key issue is the optimal design of the lateral load resisting system. This paper focuses on the optimal design of regular, concentric braced frame (CBF) multi-storey steel building structures. The optimal configurations are determined by a numerical method using genetic algorithm approach, developed by the authors. Aim is to find structural configurations with minimum structural cost. The design constraints of objective function are assigned in accordance with Eurocode 3 and Eurocode 8 guidelines. In this paper the results are presented for various building geometries, different seismic intensities, and levels of energy dissipation.

Keywords: Dissipative Structures, Genetic Algorithm, Seismic Effects, Structural Optimization.

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Authors: M. Emami, R. Tarighi, R. Goodarzi

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Maximal radar wave absorbing cannot be achieved by shaping alone. We have to focus on the parameters of absorbing materials such as permittivity, permeability, and thickness so that best absorbing according to our necessity can happen. The real and imaginary parts of the relative complex permittivity (ε_r' and ε_r") and permeability (µ_r' and µ_r") were obtained by simulation. The microwave absorbing property of carbon and Ni(C) is simulated in this study by MATLAB software; the simulation was in the frequency range between 2 to 12 GHz for carbon black (C), and carbon coated nickel (Ni(C)) with different thicknesses. In fact, we draw reflection loss (RL) for C and Ni-C via frequency. We have compared their absorption for 3-mm thickness and predicted for other thicknesses by using of electromagnetic wave transmission theory. The results showed that reflection loss position changes in low frequency with increasing of thickness. We found out that, in all cases, using nanocomposites as absorbance cannot get better results relative to pure nanoparticles. The frequency where absorption is maximum can determine the best choice between nanocomposites and pure nanoparticles. Also, we could find an optimal thickness for long wavelength absorbing in order to utilize them in protecting shields and covering.

Keywords: Absorbing, carbon, carbon nickel, frequency, thicknesses.

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Authors: Sanjeev Kumar, S. K. Nath

Abstract:

Proper selection of welding parameters for getting excellent weld is a challenge. HAZ simulation helps in identifying suitable welding parameters like heating rate, cooling rate, peak temperature, and energy input. In this study, the influence of weld thermal cycle of heat affected zone (HAZ) is simulated for Submerged Arc Welding (SAW) using Gleeble ® 3800 thermomechanical simulator. A (Micro-alloyed) MA steel plate of thickness 18 mm having yield strength 450MPa is used for making test specimens. Determination of the mechanical properties of weld simulated specimens including Charpy V-notch toughness and hardness is performed. Peak temperatures of 1300°C, 1150°C, 1000°C, 900°C, 800°C, heat energy input of 22KJ/cm and preheat temperatures of 30°C have been used with Rykalin-3D simulation model. It is found that the impact toughness (75J) is the best for the simulated HAZ specimen at the peak temperature 900ºC. For parent steel, impact toughness value is 26.8J at -50°C in transverse direction.

Keywords: HAZ Simulation, Mechanical Properties, Peak Temperature, Ship hull steel, and Weldability.

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Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD^® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: Extra vehicular activity, biomechanics, inverse kinematics, human body modeling.

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Authors: H. Arabi, A.R. Kamali Asl

Abstract:

The purpose of this work is measurement of the system presampling MTF of a variable resolution x-ray (VRX) CT scanner. In this paper, we used the parameters of an actual VRX CT scanner for simulation and study of effect of different focal spot sizes on system presampling MTF by Monte Carlo method (GATE simulation software). Focal spot size of 0.6 mm limited the spatial resolution of the system to 5.5 cy/mm at incident angles of below 17º for cell#1. By focal spot size of 0.3 mm the spatial resolution increased up to 11 cy/mm and the limiting effect of focal spot size appeared at incident angles of below 9º. The focal spot size of 0.3 mm could improve the spatial resolution to some extent but because of magnification non-uniformity, there is a 10 cy/mm difference between spatial resolution of cell#1 and cell#256. The focal spot size of 0.1 mm acted as an ideal point source for this system. The spatial resolution increased to more than 35 cy/mm and at all incident angles the spatial resolution was a function of incident angle. By the way focal spot size of 0.1 mm minimized the effect of magnification nonuniformity.

Keywords: Focal spot, Spatial resolution, Monte Carlosimulation, Variable resolution x-ray (VRX) CT.

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Authors: Paola Lecca

Abstract:

Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.

Keywords: Mathematical structure, algorithmic implementation, biochemical network models.

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Authors: Jianjun Yuan, Changjun Jiang

Abstract:

Pairwise testing, which requires that every combination of valid values of each pair of system factors be covered by at lease one test case, plays an important role in software testing since many faults are caused by unexpected 2-way interactions among system factors. Although meta-heuristic strategies like simulated annealing can generally discover smaller pairwise test suite, they may cost more time to perform search, compared with greedy algorithms. We propose a new method, improved Extremal Optimization (EO) based on the Bak-Sneppen (BS) model of biological evolution, for constructing pairwise test suites and define fitness function according to the requirement of improved EO. Experimental results show that improved EO gives similar size of resulting pairwise test suite and yields an 85% reduction in solution time over SA.

Keywords: Covering Arrays, Extremal Optimization, Simulated Annealing, Software Testing.

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Authors: M. Rossini, A. Portioli Studacher

Abstract:

The market competition is moving from the single firm to the whole supply chain because of increasing competition and growing need for operational efficiencies and customer orientation. Supply chain management allows companies to look beyond their organizational boundaries to develop and leverage resources and capabilities of their supply chain partners. This creates competitive advantages in the marketplace and because of this SCM has acquired strategic importance. Lean Approach is a management strategy that focuses on reducing every type of waste present in an organization. This approach is becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In particular, it is not well studied which are the impacts of lean approach principles in a supply chain context. In literature there are only few studies aimed at understanding the qualitative impact of the lean approach in supply chains. Therefore, the goal of this research work is to study the impacts of lean principles implementation along a supply chain. To achieve this, a simulation model of a threeechelon multi-product supply chain has been built. Kanban system (and several priority policies) and setup time reduction degrees are implemented in the lean-configured supply chain to apply pull and lot-sizing decrease principles respectively. To evaluate the benefits of lean approach, lean supply chain is compared with an EOQ-configured supply chain. The simulation results show that Kanban system and setup-time reduction improve inventory stock level. They also show that logistics efforts are affected to lean implementation degree. The paper concludes describing performances of lean supply chain in different contexts.

Keywords: Inventory policy, Kanban, lean supply chain, simulation study, supply chain management, planning.

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Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

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Authors: P. Subbaraj, V. Rajasekaran

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This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

Keywords: Combined ANN, Evolutionary Programming, Particle Swarm Optimization, Genetic Algorithm and Peak load forecasting.

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Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: Image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform.

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Authors: Mohamed H. Elhsnawi, Mesbah M. Salem, Saleh B. Mohamed

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Numerical simulation performed to investigate the behavior of the high pressure hydrogen jetting of air. High pressure hydrogen (30–40 MPa) was injected to air at atmospheric pressure through 2mm orifice. Numerical simulations were performed with Kiva3V code with 2D axisymmetric geometry. Numerical simulations showed that auto ignition of high pressure hydrogen to air are possible due to molecular diffusion. Auto ignition was predicted at hydrogen-air contact surface due to mass and energy exchange between high temperature hydrogen and air heated by shock wave.

Keywords: Spontaneous Ignition, Diffusion Ignition, Hydrogen ignition, Hydrogen Jet.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: Xin Zhao, Yin-fan Zhu, Wei-ping Wang, Qun Li

Abstract:

The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.

Keywords: Time-sliced influence diagrams, discrete event systems, dynamic-stochastic influence diagrams, modeling formalism, simulation algorithm.

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