Search results for: genetic gain
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1348

Search results for: genetic gain

988 Genetic-Based Multi Resolution Noisy Color Image Segmentation

Authors: Raghad Jawad Ahmed

Abstract:

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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987 A Study on the Assessment of Prosthetic Infection after Total Knee Replacement Surgery

Authors: Chang, Chun-Lang, Liu, Chun-Kai

Abstract:

This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimization, the weight of each factor is calculated and obtained. In the meantime, Excel VBA and Case Based Reasoning are combined and adopted to evaluate the system. Results show no significant difference found through Genetic Algorithm Logistic Regression and Particle Swarm Optimization with over 97% accuracy in both methods. Both ROC areas are above 0.87. This study can provide critical reference to medical personnel as clinical assessment to effectively enhance medical care quality and efficiency, prevent unnecessary waste, and provide practical advantages to resource allocation to medical institutes.

Keywords: Total knee replacement, Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization.

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986 Metaheuristics Methods (GA and ACO) for Minimizing the Length of Freeman Chain Code from Handwritten Isolated Characters

Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz

Abstract:

This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.

Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.

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985 Identification of Single Nucleotide Polymorphism in 5'-UTR of CYP11B1 Gene in Pakistani Sahiwal Cattle

Authors: S. Manzoor, A. Nadeem, M. Javed, ME. Babar

Abstract:

A major goal in animal genetics is to understand the role of common genetic variants in diseases susceptibility and production traits. Sahiwal cattle can be considered as a global animal genetic resource due to its relatively high milk producing ability, resistance against tropical diseases and heat tolerant. CYP11B1 gene provides instructions for making a mitochondrial enzyme called steroid 11-beta-hydroxylase. It catalyzes the 11deoxy-cortisol to cortisol and 11deoxycorticosterone to corticosterone in cattle. The bovine CYP11B1 gene is positioned on BTA14q12 comprises of eight introns and nine exons and protein is associated with mitochondrial epithelium. The present study was aimed to identify the single-nucleotide polymorphisms in CYP11B1 gene in Sahiwal cattle breed of Pakistan. Four polymorphic sites were identified in exon one of CYP11B1 gene through sequencing approach. Significant finding was the incidence of the C→T polymorphism in 5'-UTR, causing amino acid substitution from alanine to valine (A30V) in Sahiwal cattle breed. That Ala/Val polymorphism may serve as a powerful genetic tool for the development of DNA markers that can be used for the particular traits for different local cattle breeds.

Keywords: CYP11B1, single nucleotide polymorphism, sahiwal cattle, Pakistan.

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984 Generational PipeLined Genetic Algorithm (PLGA)using Stochastic Selection

Authors: Malay K. Pakhira, Rajat K. De

Abstract:

In this paper, a pipelined version of genetic algorithm, called PLGA, and a corresponding hardware platform are described. The basic operations of conventional GA (CGA) are made pipelined using an appropriate selection scheme. The selection operator, used here, is stochastic in nature and is called SA-selection. This helps maintaining the basic generational nature of the proposed pipelined GA (PLGA). A number of benchmark problems are used to compare the performances of conventional roulette-wheel selection and the SA-selection. These include unimodal and multimodal functions with dimensionality varying from very small to very large. It is seen that the SA-selection scheme is giving comparable performances with respect to the classical roulette-wheel selection scheme, for all the instances, when quality of solutions and rate of convergence are considered. The speedups obtained by PLGA for different benchmarks are found to be significant. It is shown that a complete hardware pipeline can be developed using the proposed scheme, if parallel evaluation of the fitness expression is possible. In this connection a low-cost but very fast hardware evaluation unit is described. Results of simulation experiments show that in a pipelined hardware environment, PLGA will be much faster than CGA. In terms of efficiency, PLGA is found to outperform parallel GA (PGA) also.

Keywords: Hardware evaluation, Hardware pipeline, Optimization, Pipelined genetic algorithm, SA-selection.

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983 Screening Wheat Parents of Mapping Population for Heat and Drought Tolerance, Detection of Wheat Genetic Variation

Authors: H.R. Balouchi

Abstract:

To evaluate genetic variation of wheat (Triticum aestivum) affected by heat and drought stress on eight Australian wheat genotypes that are parents of Doubled Haploid (HD) mapping populations at the vegetative stage, the water stress experiment was conducted at 65% field capacity in growth room. Heat stress experiment was conducted in the research field under irrigation over summer. Result show that water stress decreased dry shoot weight and RWC but increased osmolarity and means of Fv/Fm values in all varieties except for Krichauff. Krichauff and Kukri had the maximum RWC under drought stress. Trident variety was shown maximum WUE, osmolarity (610 mM/Kg), dry mater, quantum yield and Fv/Fm 0.815 under water stress condition. However, the recovery of quantum yield was apparent between 4 to 7 days after stress in all varieties. Nevertheless, increase in water stress after that lead to strong decrease in quantum yield. There was a genetic variation for leaf pigments content among varieties under heat stress. Heat stress decreased significantly the total chlorophyll content that measured by SPAD. Krichauff had maximum value of Anthocyanin content (2.978 A/g FW), chlorophyll a+b (2.001 mg/g FW) and chlorophyll a (1.502 mg/g FW). Maximum value of chlorophyll b (0.515 mg/g FW) and Carotenoids (0.234 mg/g FW) content belonged to Kukri. The quantum yield of all varieties decreased significantly, when the weather temperature increased from 28 ÔùªC to 36 ÔùªC during the 6 days. However, the recovery of quantum yield was apparent after 8th day in all varieties. The maximum decrease and recovery in quantum yield was observed in Krichauff. Drought and heat tolerant and moderately tolerant wheat genotypes were included Trident, Krichauff, Kukri and RAC875. Molineux, Berkut and Excalibur were clustered into most sensitive and moderately sensitive genotypes. Finally, the results show that there was a significantly genetic variation among the eight varieties that were studied under heat and water stress.

Keywords: Abiotic stress, genetic variation, fluorescence, wheat genotypes.

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982 Effect of a Linear-Exponential Penalty Functionon the GA-s Efficiency in Optimization of a Laminated Composite Panel

Authors: A. Abedian, M. H. Ghiasi, B. Dehghan-Manshadi

Abstract:

A stiffened laminated composite panel (1 m length × 0.5m width) was optimized for minimum weight and deflection under several constraints using genetic algorithm. Here, a significant study on the performance of a penalty function with two kinds of static and dynamic penalty factors was conducted. The results have shown that linear dynamic penalty factors are more effective than the static ones. Also, a specially combined linear-exponential function has shown to perform more effective than the previously mentioned penalty functions. This was then resulted in the less sensitivity of the GA to the amount of penalty factor.

Keywords: Genetic algorithms, penalty function, stiffenedcomposite panel, finite element method.

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981 Fixture Layout Optimization Using Element Strain Energy and Genetic Algorithm

Authors: Zeshan Ahmad, Matteo Zoppi, Rezia Molfino

Abstract:

The stiffness of the workpiece is very important to reduce the errors in manufacturing process. The high stiffness of the workpiece can be achieved by optimal positioning of fixture elements in the fixture. The minimization of the sum of the nodal deflection normal to the surface is used as objective function in previous research. The deflection in other direction has been neglected. The 3-2-1 fixturing principle is not valid for metal sheets due to its flexible nature. We propose a new fixture layout optimization method N-3-2-1 for metal sheets that uses the strain energy of the finite elements. This method combines the genetic algorithm and finite element analysis. The objective function in this method is to minimize the sum of all the element strain energy. By using the concept of element strain energy, the deformations in all the directions have been considered. Strain energy and stiffness are inversely proportional to each other. So, lower the value of strain energy, higher will be the stiffness. Two different kinds of case studies are presented. The case studies are solved for both objective functions; element strain energy and nodal deflection. The result are compared to verify the propose method.

Keywords: Fixture layout, optimization, fixturing element, genetic algorithm.

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980 Relay Node Placement for Connectivity Restoration in Wireless Sensor Networks Using Genetic Algorithms

Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

Abstract:

Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: Connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks.

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979 Design of Low Noise Amplifiers for 10 GHz Application

Authors: Makesh Iyer, T. Shanmuganantham

Abstract:

This work deals with the designing of an efficient low noise amplifier for 10.00 GHz applications. The amplifier is designed using Gallium Arsenide High Electron Mobility Transistor (GaAs HEMT) ATF – 36077 with inductive source degeneration technique which is one of the techniques to improve the stability of the potentially unstable device and make it unconditionally stable. Also, different substrates are used for designing the LNA to identify the suitable substrate that gives optimum results. It is observed that the noise immunity is more in Low Noise Amplifier (LNA) designed using RT Duroid 5880 substrate. This design resulted in noise figure of 0.859 dB and power gain of 15.530 dB. The comparative analysis of the LNA design is discussed in this paper.

Keywords: Low noise amplifier, substrate, distributed components, gain, noise figure.

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978 Opponent Color and Curvelet Transform Based Image Retrieval System Using Genetic Algorithm

Authors: Yesubai Rubavathi Charles, Ravi Ramraj

Abstract:

In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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977 PUMA 560 Optimal Trajectory Control using Genetic Algorithm, Simulated Annealing and Generalized Pattern Search Techniques

Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

Robot manipulators are highly coupled nonlinear systems, therefore real system and mathematical model of dynamics used for control system design are not same. Hence, fine-tuning of controller is always needed. For better tuning fast simulation speed is desired. Since, Matlab incorporates LAPACK to increase the speed and complexity of matrix computation, dynamics, forward and inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in such a way that all operations are matrix based which give very less simulation time. This paper compares PID parameter tuning using Genetic Algorithm, Simulated Annealing, Generalized Pattern Search (GPS) and Hybrid Search techniques. Controller performances for all these methods are compared in terms of joint space ITSE and cartesian space ISE for tracking circular and butterfly trajectories. Disturbance signal is added to check robustness of controller. GAGPS hybrid search technique is showing best results for tuning PID controller parameters in terms of ITSE and robustness.

Keywords: Controller Tuning, Genetic Algorithm, Pattern Search, Robotic Controller, Simulated Annealing.

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976 Parameters Identification of Mathematical Model of the Fission Yeast Cell Cycle Control Using Evolutionary Strategy

Authors: A. Ghaffari, A. S. Mostafavi

Abstract:

Complex assemblies of interacting proteins carry out most of the interesting jobs in a cell, such as metabolism, DNA synthesis, mitosis and cell division. These physiological properties play out as a subtle molecular dance, choreographed by underlying regulatory networks that control the activities of cyclin-dependent kinases (CDK). The network can be modeled by a set of nonlinear differential equations and its behavior predicted by numerical simulation. In this paper, an innovative approach has been proposed that uses genetic algorithms to mine a set of behavior data output by a biological system in order to determine the kinetic parameters of the system. In our approach, the machine learning method is integrated with the framework of existent biological information in a wiring diagram so that its findings are expressed in a form of system dynamic behavior. By numerical simulations it has been illustrated that the model is consistent with experiments and successfully shown that such application of genetic algorithms will highly improve the performance of mathematical model of the cell division cycle to simulate such a complicated bio-system.

Keywords: Cell cycle, Cyclin-dependent kinase, Fission yeast, Genetic algorithms, Mathematical modeling, Wiring diagram

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975 Optimizing PID Parameters Using Harmony Search

Authors: N. Arulanand, P. Dhara

Abstract:

Optimizing the parameters in the controller plays a vital role in the control theory and its applications. Optimizing the PID parameters is finding out the best value from the feasible solutions. Finding the optimal value is an optimization problem. Inverted Pendulum is a very good platform for control engineers to verify and apply different logics in the field of control theory. It is necessary to find an optimization technique for the controller to tune the values automatically in order to minimize the error within the given bounds. In this paper, the algorithmic concepts of Harmony search (HS) and Genetic Algorithm (GA) have been analyzed for the given range of values. The experimental results show that HS performs well than GA.

Keywords: Genetic Algorithm, Harmony Search Algorithm, Inverted Pendulum, PID Controller.

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974 An Improved GA to Address Integrated Formulation of Project Scheduling and Material Ordering with Discount Options

Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: Genetic algorithm, material ordering, project management, project scheduling.

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973 Clustering Approach to Unveiling Relationships between Gene Regulatory Networks

Authors: Hiba Hasan, Khalid Raza

Abstract:

Reverse engineering of genetic regulatory network involves the modeling of the given gene expression data into a form of the network. Computationally it is possible to have the relationships between genes, so called gene regulatory networks (GRNs), that can help to find the genomics and proteomics based diagnostic approach for any disease. In this paper, clustering based method has been used to reconstruct genetic regulatory network from time series gene expression data. Supercoiled data set from Escherichia coli has been taken to demonstrate the proposed method.

Keywords: Gene expression, gene regulatory networks (GRNs), clustering, data preprocessing, network visualization.

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972 Predicting Residence Time of Pollutants in Transient Storage Zones of Rivers by Genetic Programming

Authors: Rajeev R. Sahay

Abstract:

Rivers have transient storage or dead zones where injected pollutants or solutes are entrapped for considerable period of time, known as residence time, before being released into the main flowing zones of rivers. In this study, a new empirical expression for residence time, implementing genetic programming on published dispersion data, has been derived. The proposed expression uses few hydraulic and geometric characteristics of rivers which are normally known to the authorities. When compared with some reported expressions, based on various statistical indices, it can be concluded that the proposed expression predicts the residence time of pollutants in natural rivers more accurately.

Keywords: Parameter estimation, pollutant transport, residence time, rivers, transient storage.

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971 Physicians’ Knowledge and Perception of Gene Profiling in Malaysia

Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

Abstract:

Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires were returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age ranges from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge; however, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non- significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: Gene Profiling, Knowledge, Malaysia, Physician.

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970 Analysis of Nonlinear Pulse Propagation Characteristics in Semiconductor Optical Amplifier for Different Input Pulse Shapes

Authors: Suchi Barua, Narottam Das, Sven Nordholm, Mohammad Razaghi

Abstract:

This paper presents nonlinear pulse propagation characteristics for different input optical pulse shapes with various input pulse energy levels in semiconductor optical amplifiers. For simulation of nonlinear pulse propagation, finite-difference beam propagation method is used to solve the nonlinear Schrödinger equation. In this equation, gain spectrum dynamics, gain saturation are taken into account which depends on carrier depletion, carrier heating, spectral-hole burning, group velocity dispersion, self-phase modulation and two photon absorption. From this analysis, we obtained the output waveforms and spectra for different input pulse shapes as well as for different input energies. It shows clearly that the peak position of the output waveforms are shifted toward the leading edge which due to the gain saturation of the SOA for higher input pulse energies. We also analyzed and compared the normalized difference of full-width at half maximum for different input pulse shapes in the SOA.

Keywords: Finite-difference beam propagation method, pulse shape, pulse propagation, semiconductor optical amplifier.

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969 The Haar Wavelet Transform of the DNA Signal Representation

Authors: Abdelkader Magdy, Magdy Saeb, A. Baith Mohamed, Ahmed Khadragi

Abstract:

The Deoxyribonucleic Acid (DNA) which is a doublestranded helix of nucleotides consists of: Adenine (A), Cytosine (C), Guanine (G) and Thymine (T). In this work, we convert this genetic code into an equivalent digital signal representation. Applying a wavelet transform, such as Haar wavelet, we will be able to extract details that are not so clear in the original genetic code. We compare between different organisms using the results of the Haar wavelet Transform. This is achieved by using the trend part of the signal since the trend part bears the most energy of the digital signal representation. Consequently, we will be able to quantitatively reconstruct different biological families.

Keywords: Digital Signal, DNA, Fluctuation part, Haar wavelet, Nucleotides, Trend part.

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968 Solving the Flexible Job Shop Scheduling Problem with Uniform Processing Time Uncertainty

Authors: Nasr Al-Hinai, Tarek Y. ElMekkawy

Abstract:

The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.

Keywords: Genetic algorithm, met-heuristic, robust scheduling, uncertainty of processing times

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967 Solving Part Type Selection and Loading Problem in Flexible Manufacturing System Using Real Coded Genetic Algorithms – Part I: Modeling

Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper and its companion (Part 2) deal with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system-s efficiency and productivity. The complexity of the problems is harder when flexibilities of operations such as the possibility of operation processed on alternative machines with alternative tools are considered. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. These real numbers can be converted into part type sequence and machines that are used to process the part types. This first part of the papers focuses on the modeling of the problems and discussing how the novel chromosome representation can be applied to solve the problems. The second part will discuss the effectiveness of the RCGA to solve various test bed problems.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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966 Students as Global Citizens: Lessons from the International Study Tour

Authors: Ana Hol

Abstract:

Study and work operations are being transformed with the uses of technologies and are consequently becoming global. This paper outlines lessons learned based on the international study tour that Australian Bachelor of Information Systems students undertook. This research identifies that for the study tour to be successful, students need to gain skills that global citizens require. For example, students will need to gain an understanding of local cultures, local customs and habits. Furthermore, students would also need to gain an understanding of how a field of their future career expertise operates in the host country, how study and business are conducted internationally, which tools and technologies are currently being utilized on a global scale, what trends drive future developments world-wide and how business negotiations and collaborations are being undertaken across borders. Furthermore, this research provides a guide to educators who are planning, guiding and running study tours as it outlines the requirements of having a pre-tour preparatory session, carefully planned and executed tour itineraries and post-tour sessions during which students can reflect on their experiences and lessons learned so that they can apply them to future international business visits and ventures.

Keywords: Global education, international experiences, international study tours, students as global citizens, student centered education.

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965 Design and Implementation of Optimal Winner Determination Algorithm in Combinatorial e- Auctions

Authors: S. Khanpour, A. Movaghar

Abstract:

The one of best robust search technique on large scale search area is heuristic and meta heuristic approaches. Especially in issue that the exploitation of combinatorial status in the large scale search area prevents the solution of the problem via classical calculating methods, so such problems is NP-complete. in this research, the problem of winner determination in combinatorial auctions have been formulated and by assessing older heuristic functions, we solve the problem by using of genetic algorithm and would show that this new method would result in better performance in comparison to other heuristic function such as simulated annealing greedy approach.

Keywords: Bids, genetic algorithm, heuristic, metaheuristic, simulated annealing greedy.

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964 Parallel Joint Channel Coding and Cryptography

Authors: Nataša Živić, Christoph Ruland

Abstract:

Method of Parallel Joint Channel Coding and Cryptography has been analyzed and simulated in this paper. The method is an extension of Soft Input Decryption with feedback, which is used for improvement of channel decoding of secured messages. Parallel Joint Channel Coding and Cryptography results in improved coding gain of channel decoding, which achieves more than 2 dB. Such results are an implication of a combination of receiver components and their interoperability.

Keywords: Block length, Coding gain, Feedback, L-values, Parallel Joint Channel Coding and Cryptography, Soft Input Decryption.

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963 Cereals' Products with Red Grape and Walnut Extracts as Functional Foods for Prevention of Kidney Dysfunction

Authors: Sahar Y. Al-Okbi, Doha A. Mohamed, Thanaa E. Hamed, Ahmed Ms Hussein

Abstract:

In the present research, two nutraceuticals made from red grape and walnut that showed previously to improve kidney dysfunction were incorporated separately into functional foods' bread made from barley and rice bran. The functional foods were evaluated in rats in which chronic renal failure was induced through feeding diet rich in adenine and phosphate (APD). The evaluation based on assessing kidney function, oxidative stress, inflammatory biomarkers and body weight gain. Results showed induction of chronic kidney failure reflected in significant increase in plasma urea, creatinine, malondialdehyde, tumor necrosis factor- α and low density lipoprotein cholesterol along with significant reduction of plasma albumin, and total antioxidant and creatinine clearance and body weight gain on feeding APD compared to control healthy group. Feeding the functional foods produced amelioration in the different biochemical parameters and body weight gain indicating improvement in kidney function.

Keywords: Functional food, kidney dysfunction, rats.

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962 A Quadcopter Stability Analysis: A Case Study Using Simulation

Authors: C. S. Bianca Sabrina, N. Egidio Raimundo, L. Alexandre Baratella, C. H. João Paulo

Abstract:

This paper aims to present a study, with the theoretical concepts and applications of the Quadcopter, using the MATLAB simulator. In order to use this tool, the study of the stability of the drone through a Proportional - Integral - Derivative (PID) controller will be presented. After the stability study, some tests are done on the simulator and its results will be presented. From the mathematical model, it is possible to find the Newton-Euler angles, so that it is possible to stabilize the quadcopter in a certain position in the air, starting from the ground. In order to understand the impact of the controllers gain values on the stabilization of the Euler-Newton angles, three conditions will be tested with different controller gain values.

Keywords: Controllers, drones, quadcopter, stability.

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961 Optimisation of Structural Design by Integrating Genetic Algorithms in the Building Information Modelling Environment

Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

Abstract:

Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: Building Information Modelling, BIM, Genetic Algorithm, GA, architecture-engineering-construction, AEC, Optimisation, structure, design, population, generation, selection, mutation, crossover, offspring.

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960 Evolutionary Search Techniques to Solve Set Covering Problems

Authors: Darwin Gouwanda, S. G. Ponnambalam

Abstract:

Set covering problem is a classical problem in computer science and complexity theory. It has many applications, such as airline crew scheduling problem, facilities location problem, vehicle routing, assignment problem, etc. In this paper, three different techniques are applied to solve set covering problem. Firstly, a mathematical model of set covering problem is introduced and solved by using optimization solver, LINGO. Secondly, the Genetic Algorithm Toolbox available in MATLAB is used to solve set covering problem. And lastly, an ant colony optimization method is programmed in MATLAB programming language. Results obtained from these methods are presented in tables. In order to assess the performance of the techniques used in this project, the benchmark problems available in open literature are used.

Keywords: Set covering problem, genetic algorithm, ant colony optimization, LINGO.

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959 Thermodynamic Optimization of Turboshaft Engine using Multi-Objective Genetic Algorithm

Authors: S. Farahat, E. Khorasani Nejad, S. M. Hoseini Sarvari

Abstract:

In this paper multi-objective genetic algorithms are employed for Pareto approach optimization of ideal Turboshaft engines. In the multi-objective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are specific thrust (F/m& 0), specific fuel consumption ( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O η . These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters (compressor pressure ratio, turbine temperature ratio and Mach number). At the first stage single objective optimization has been investigated and the method of NSGA-II has been used for multiobjective optimization. Optimization procedures are performed for two and four objective functions and the results are compared for ideal Turboshaft engine. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of four objective optimization the results are given in tables.

Keywords: Multi-objective, Genetic algorithm, Turboshaft Engine.

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