Search results for: genetic polymorphisms
1366 A Hybrid ICA-GA Algorithm for Solving Multiobjective Optimization of Production Planning Problems
Authors: Omar Ramzi Jasim, Jalal Sultan Ashour
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Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problems in operation and it can potentially lead to poor customer satisfaction. In this paper, a hybrid evolutionary algorithm (ICA-GA) is presented, which integrates the merits of both imperialist competitive algorithm (ICA) and genetic algorithm (GA) for solving multi-objective MPS problems. In the presented algorithm, the colonies in each empire has be represented a small population and communicate with each other using genetic operators. By testing on 5 production scenarios, the numerical results of ICA-GA algorithm show the efficiency and capabilities of the hybrid algorithm in finding the optimum solutions. The ICA-GA solutions yield the lower inventory level and keep customer satisfaction high and the required overtime is also lower, compared with results of GA and SA in all production scenarios.Keywords: master production scheduling, genetic algorithm, imperialist competitive algorithm, hybrid algorithm
Procedia PDF Downloads 4671365 A Comparison of Sequential Quadratic Programming, Genetic Algorithm, Simulated Annealing, Particle Swarm Optimization for the Design and Optimization of a Beam Column
Authors: Nima Khosravi
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This paper describes an integrated optimization technique with concurrent use of sequential quadratic programming, genetic algorithm, and simulated annealing particle swarm optimization for the design and optimization of a beam column. In this research, the comparison between 4 different types of optimization methods. The comparison is done and it is found out that all the methods meet the required constraints and the lowest value of the objective function is achieved by SQP, which was also the fastest optimizer to produce the results. SQP is a gradient based optimizer hence its results are usually the same after every run. The only thing which affects the results is the initial conditions given. The initial conditions given in the various test run were very large as compared. Hence, the value converged at a different point. Rest of the methods is a heuristic method which provides different values for different runs even if every parameter is kept constant.Keywords: beam column, genetic algorithm, particle swarm optimization, sequential quadratic programming, simulated annealing
Procedia PDF Downloads 3841364 Effectiveness of ISSR Technique in Revealing Genetic Diversity of Phaseolus vulgaris L. Representing Various Parts of the World
Authors: Mohamed El-Shikh
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Phaseolus vulgaris L. is the world’s second most important bean after soybeans; used for human food and animal feed. It has generally been linked to reduced risk of cardiovascular disease, diabetes mellitus, obesity, cancer and diseases of digestive tract. The effectiveness of ISSR in achievement of the genetic diversity among 60 common bean accessions; represent various germplasms around the world was investigated. In general, the studied Phaseolus vulgaris accessions were divided into 2 major groups. All of the South-American accessions were separated into the second major group. These accessions may have different genetic features that are distinct from the rest of the accessions clustered in the major group. Asia and Europe accessions (1-20) seem to be more genetically similar (99%) to each other as they clustered in the same sub-group. The American and African varieties showed similarities as well and clustered in the same sub-tree group. In contrast, Asian and American accessions No. 22 and 23 showed a high level of genetic similarities, although these were isolated from different regions. The phylogenetic tree showed that all the Asian accessions (along with Australian No. 59 and 60) were similar except Indian and Yemen accessions No. 9 and 20. Only Netherlands accession No. 3 was different from the rest of European accessions. Morocco accession No. 52 was genetically different from the rest of the African accessions. Canadian accession No. 44 seems to be different from the other North American accessions including Guatemala, Mexico and USA.Keywords: phylogenetic tree, Phaseolus vulgaris, ISSR technique, genetics
Procedia PDF Downloads 4071363 Genetic Algorithm Optimization of a Small Scale Natural Gas Liquefaction Process
Authors: M. I. Abdelhamid, A. O. Ghallab, R. S. Ettouney, M. A. El-Rifai
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An optimization scheme based on COM server is suggested for communication between Genetic Algorithm (GA) toolbox of MATLAB and Aspen HYSYS. The structure and details of the proposed framework are discussed. The power of the developed scheme is illustrated by its application to the optimization of a recently developed natural gas liquefaction process in which Aspen HYSYS was used for minimization of the power consumption by optimizing the values of five operating variables. In this work, optimization by coupling between the GA in MATLAB and Aspen HYSYS model of the same process using the same five decision variables enabled improvements in power consumption by 3.3%, when 77% of the natural gas feed is liquefied. Also on inclusion of the flow rates of both nitrogen and carbon dioxide refrigerants as two additional decision variables, the power consumption decreased by 6.5% for a 78% liquefaction of the natural gas feed.Keywords: stranded gas liquefaction, genetic algorithm, COM server, single nitrogen expansion, carbon dioxide pre-cooling
Procedia PDF Downloads 4461362 Understanding Different Facets of Chromosome Abnormalities: A 17-year Cytogenetic Study and Indian Perspectives
Authors: Lakshmi Rao Kandukuri, Mamata Deenadayal, Suma Prasad, Bipin Sethi, Srinadh Buragadda, Lalji Singh
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Worldwide; at least 7.6 million children are born annually with severe genetic or congenital malformations and among them 90% of these are born in mid and low-income countries. Precise prevalence data are difficult to collect, especially in developing countries, owing to the great diversity of conditions and also because many cases remain undiagnosed. The genetic and congenital disorder is the second most common cause of infant and childhood mortality and occurs with a prevalence of 25-60 per 1000 births. The higher prevalence of genetic diseases in a particular community may, however, be due to some social or cultural factors. Such factors include the tradition of consanguineous marriage, which results in a higher rate of autosomal recessive conditions including congenital malformations, stillbirths, or mental retardation. Genetic diseases can vary in severity, from being fatal before birth to requiring continuous management; their onset covers all life stages from infancy to old age. Those presenting at birth are particularly burdensome and may cause early death or life-long chronic morbidity. Genetic testing for several genetic diseases identifies changes in chromosomes, genes, or proteins. The results of a genetic test can confirm or rule out a suspected genetic condition or help determine a person's chance of developing or passing on a genetic disorder. Several hundred genetic tests are currently in use and more are being developed. Chromosomal abnormalities are the major cause of human suffering, which are implicated in mental retardation, congenital malformations, dysmorphic features, primary and secondary amenorrhea, reproductive wastage, infertility neoplastic diseases. Cytogenetic evaluation of patients is helpful in the counselling and management of affected individuals and families. We present here especially chromosomal abnormalities which form a major part of genetic disease burden in India. Different programmes on chromosome research and human reproductive genetics primarily relate to infertility since this is a major public health problem in our country, affecting 10-15 percent of couples. Prenatal diagnosis of chromosomal abnormalities in high-risk pregnancies helps in detecting chromosomally abnormal foetuses. Such couples are counselled regarding the continuation of pregnancy. In addition to the basic research, the team is providing chromosome diagnostic services that include conventional and advanced techniques for identifying various genetic defects. Other than routine chromosome diagnosis for infertility, also include patients with short stature, hypogonadism, undescended testis, microcephaly, delayed developmental milestones, familial, and isolated mental retardation, and cerebral palsy. Thus, chromosome diagnostics has found its applicability not only in disease prevention and management but also in guiding the clinicians in certain aspects of treatment. It would be appropriate to affirm that chromosomes are the images of life and they unequivocally mirror the states of human health. The importance of genetic counseling is increasing with the advancement in the field of genetics. The genetic counseling can help families to cope with emotional, psychological, and medical consequences of genetic diseases.Keywords: India, chromosome abnormalities, genetic disorders, cytogenetic study
Procedia PDF Downloads 3151361 Scheduling of Repetitive Activities for Height-Rise Buildings: Optimisation by Genetic Algorithms
Authors: Mohammed Aljoma
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In this paper, a developed prototype for the scheduling of repetitive activities in height-rise buildings was presented. The activities that describe the behavior of the most of activities in multi-storey buildings are scheduled using the developed approach. The prototype combines three methods to attain the optimized planning. The methods include Critical Path Method (CPM), Gantt and Line of Balance (LOB). The developed prototype; POTER is used to schedule repetitive and non-repetitive activities with respect to all constraints that can be automatically generated using a generic database. The prototype uses the method of genetic algorithms for optimizing the planning process. As a result, this approach enables contracting organizations to evaluate various planning solutions that are calculated, tested and classified by POTER to attain an optimal time-cost equilibrium according to their own criteria of time or coast.Keywords: planning scheduling, genetic algorithms, repetitive activity, construction management, planning, scheduling, risk management, project duration
Procedia PDF Downloads 3061360 Genetic Polymorphism in the Vitamin D Receptor Gene and 25-Hydroxyvitamin D Serum Levels in East Indian Women with Polycystic Ovary Syndrome
Authors: Dipanshu Sur, Ratnabali Chakravorty
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Background: Polycystic ovary syndrome (PCOS) is the most common metabolic abnormality such as changes in lipid profile, diabetes, hypertension and metabolic syndrome occurring in young women of reproductive age. Low vitamin D levels were found to be associated with the development of obesity and insulin resistance in women with PCOS. Variants on vitamin D receptor (VDR) gene have also been related to metabolic comorbidities in general population. Aim: The aim of this case-control study was to investigate whether the VDR gene polymorphisms are associated with susceptibility to PCOS. Methods: Women with PCOS and a control group, all aged 16-40 years, were enrolled. Genotyping of VDR Fok-I (rs2228570), VDR Apa-I (rs7975232) as well as GC (rs2282679), DHCR7 (rs12785878) SNPs between groups were determined by using direct sequencing. Serum 25-hydroxyvitamin D [25(OH)] levels were measured by ELISA. Results: Mean serum 25(OH)D in the PCOS and control samples were 19.08±7 and 23.27±6.03 (p=0.048) which were significantly lower in PCOS patients compared with controls. CC genotype of the VDR Apa-I SNP was same frequent in PCOS (25.6%) and controls (25.6%) (OR: 0.9995; 95%CI: 0.528 to 1.8921; p= 0.9987). The CC genotype was also significantly associated with both lower E2 (p=0.031) and Androstenedione levels (p=0.062). We observed a significant association of GC polymorphism with 25(OH)D levels. PCOS women carrying the GG genotype (in GC genes) had significantly higher risk for vitamin D deficiency than women carrying the TT genotype. Conclusions: In conclusion, data from this study indicate that vitamin D levels are lower, and vitamin D deficiency more frequent, in PCOS than in controls. The present findings suggest that the Apa-I, Fok-I polymorphism of the VDR gene is associated with PCOS and seems to modulate ovarian steroid secretion. Further studies are needed to better clarify the biological mechanisms by which the polymorphism influences PCOS risk.Keywords: vitamin D receptor, polymorphism, vitamin D, polycystic ovary syndrome
Procedia PDF Downloads 3031359 [Keynote Talk]: Machining Parameters Optimization with Genetic Algorithm
Authors: Dejan Tanikić, Miodrag Manić, Jelena Đoković, Saša Kalinović
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This paper deals with the determination of the optimum machining parameters, according to the measured and modelled data of the cutting temperature and surface roughness, during the turning of the AISI 4140 steel. The high cutting temperatures are unwanted occurences in the metal cutting process. They impact negatively on the quality of the machined part. The machining experiments were performed using different cutting regimes (cutting speed, feed rate and depth of cut), with different values of the workpiece hardness, which causes different values of the measured cutting temperature as well as the measured surface roughness. The temperature and surface roughness data were modelled after that using Response Surface Methodology (RSM). The obtained RSM models are used in the process of optimization of the cutting regimes using the Genetic Algorithms (GA) tool, which enables the metal cutting process in the optimum conditions.Keywords: genetic algorithms, machining parameters, response surface methodology, turning process
Procedia PDF Downloads 1851358 Phylogeography and Evolutionary History of Whiting (Merlangius merlangus) along the Turkish Coastal Waters with Comparisons to the Atlantic
Authors: Aslı Şalcıoğlu, Grigorous Krey, Raşit Bilgin
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In this study, the effect of the Turkish Straits System (TSS), comprising a biogeographical boundary that forms the connection between the Mediterranean and the Black Sea, on the evolutionary history, phylogeography and intraspecific gene flow of the whiting (Merlangius merlangus) a demersal fish species, was investigated. For these purposes, the mitochondrial DNA (CO1, cyt-b) genes were used. In addition, genetic comparisons samples from other regions (Greece, France, Atlantic) obtained from GenBank and Barcode of Life Database were made to better understand the phylogeographic history of the species at a larger geographic scale. Within this study, high level of genetic differentiation was observed along the Turkish coastal waters based on cyt-b gene, suggesting that TSS is a barrier to dispersal. Two different sub-species were also observed based on mitochondrial DNA, one found in Turkish coastal waters and Greece (M.m euxinus) and other (M.m. merlangus) in Atlantic, France.Keywords: genetic, phylogeography, TSS, whiting
Procedia PDF Downloads 3071357 Angiotensin Converting Enzyme (ACE) and Angiotensinogen (AGT) Gene Variants in Pakistani Patients of Diabetes Mellitus and Diabetic Nephropathy
Authors: Rozeena Shaikh, Syed M Shahid, Jamil Ahmad, Qaisar Mansoor, Muhammad Ismail, Abid Azhar
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Introduction: Diabetes mellitus (DM) is a prevalent non-communicable disease worldwide. In most high-income countries as well as middle-income and low- income countries. DM is among the top causes of deaths. DM may lead to many vascular complications like hypertension, nephropathy, retinopathy, neuropathy, and foot. Diabetic nephropathy (DN) characterized by persistent albuminuria is a leading cause of end stage renal failure (ESRF). Pathogenesis of diabetic nephropathy is implicated by the polymorphisms in genes encoding the components of reninangiotensin- aldosteron system (RAAS) which include angiotensinogen (AGT), angiotensin-II receptor and particularly angiotensin converting enzyme (ACE) gene. Method: Study subjects include 110 control, 110 patients with DM without hypertension, 110 patients with DM with hypertension and 110 patients with DN. Blood samples were collected for Biochemical analysis and PCR and sequencing for the specific region of both genes. Results: The frequency of DD genotype and D allele of ACE (I/D) was significantly (p<0.05) high in DM normotensive, DM hypertensive and DN patients when compared to control. The ACE G2350A genotypes and allele frequencies were significantly different (p<0.05) in DM hypertensive patients as compared to control and DN, while no difference was observed between DM normotensive and DN when compared to control. The genotypes and alleles of AGT (M268T) polymorphism were significantly different (p<0.05) in DM normotensive, DM hypertensive and DN when compared to control. Conclusion: The DD genotype and D allele of ACE (I/D), GG genotype and G allele of ACE (G2350A) and the TT genotype and T allele of AGT (M268T) polymorphism have shown a significant difference in genotype and allele frequencies between controls and patients.Keywords: genetic variations, ACE, AGT, diabetes mellitus, diabetic nephropathy, Pakistan
Procedia PDF Downloads 3911356 Credit Risk Evaluation Using Genetic Programming
Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira
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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.Keywords: credit risk assessment, rule generation, genetic programming, feature selection
Procedia PDF Downloads 3531355 Genetic Analysis of Growth Traits in White Boni Sheep under the Central Highlands Region of Yemen
Authors: Abed Al-Bial, S. Alazazie, A. Shami
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The data were collected from 1992 to 2009 of White Boni sheep maintained at the Regional Research Station in the Central Highlands of Yemen. Data were analyzed to study the growth related traits and their genetic control. The least square means for body weights were 2.26±0.67, 11.14±0.46 and 19.21±1.25 kg for birth weight (BW), weaning weight (WW), six-month weight (WM6), respectively. The pre- and post-weaning average daily weight gains (ADG1 and ADG2) were 106.04±4.98g and 46.21±8.36 g/ day. Significant differences associated with the year of lambing were observed in body weight and weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and differences tended to increase with age. Single-born lambs had a distinct advantage over those born in twin births at all stages of growth. The lambs in the dam’s second to fourth parities were generally of heavier weight and higher daily weight gain than those in other parities. The heritabilities of all body weights, weight gains at different stages of growth were moderate (0.11-0.43). The phenotypic and genetic correlation among the different body weights were positive and high. The genetic correlations of the pre- and post-weaning average daily gains with body weights were hight to moderate, except BW with ADG2.Keywords: breed, genetics, growth traits, heritability, sheep
Procedia PDF Downloads 5111354 Innovative Predictive Modeling and Characterization of Composite Material Properties Using Machine Learning and Genetic Algorithms
Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager
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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties
Procedia PDF Downloads 521353 A Genetic Algorithm Based Sleep-Wake up Protocol for Area Coverage in WSNs
Authors: Seyed Mahdi Jameii, Arash Nikdel, Seyed Mohsen Jameii
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Energy efficiency is an important issue in the field of Wireless Sensor Networks (WSNs). So, minimizing the energy consumption in this kind of networks should be an essential consideration. Sleep/wake scheduling mechanism is an efficient approach to handling this issue. In this paper, we propose a Genetic Algorithm-based Sleep-Wake up Area Coverage protocol called GA-SWAC. The proposed protocol puts the minimum of nodes in active mode and adjusts the sensing radius of each active node to decrease the energy consumption while maintaining the network’s coverage. The proposed protocol is simulated. The results demonstrate the efficiency of the proposed protocol in terms of coverage ratio, number of active nodes and energy consumption.Keywords: wireless sensor networks, genetic algorithm, coverage, connectivity
Procedia PDF Downloads 5191352 A Retrievable Genetic Algorithm for Efficient Solving of Sudoku Puzzles
Authors: Seyed Mehran Kazemi, Bahare Fatemi
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Sudoku is a logic-based combinatorial puzzle game which is popular among people of different ages. Due to this popularity, computer softwares are being developed to generate and solve Sudoku puzzles with different levels of difficulty. Several methods and algorithms have been proposed and used in different softwares to efficiently solve Sudoku puzzles. Various search methods such as stochastic local search have been applied to this problem. Genetic Algorithm (GA) is one of the algorithms which have been applied to this problem in different forms and in several works in the literature. In these works, chromosomes with little or no information were considered and obtained results were not promising. In this paper, we propose a new way of applying GA to this problem which uses more-informed chromosomes than other works in the literature. We optimize the parameters of our GA using puzzles with different levels of difficulty. Then we use the optimized values of the parameters to solve various puzzles and compare our results to another GA-based method for solving Sudoku puzzles.Keywords: genetic algorithm, optimization, solving Sudoku puzzles, stochastic local search
Procedia PDF Downloads 4211351 Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem
Authors: Nhat-To Huynh, Chen-Fu Chien
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Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing
Procedia PDF Downloads 2981350 Optimization of Hate Speech and Abusive Language Detection on Indonesian-language Twitter using Genetic Algorithms
Authors: Rikson Gultom
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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.Keywords: abusive language, hate speech, machine learning, optimization, social media
Procedia PDF Downloads 1261349 Evaluation of Genetic Fidelity and Phytochemical Profiling of Micropropagated Plants of Cephalantheropsis obcordata: An Endangered Medicinal Orchid
Authors: Gargi Prasad, Ashiho A. Mao, Deepu Vijayan, S. Mandal
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The main objective of the present study was to optimize and develop an efficient protocol for in vitro propagation of a medicinally important orchid Cephalantheropsis obcordata (Lindl.) Ormerod along with genetic stability analysis of regenerated plants. This plant has been traditionally used in Chinese folk medicine and the decoction of whole plant is known to possess anticancer activity. Nodal segments used as explants were inoculated on Murashige and Skoog (MS) medium supplemented with various concentrations of isopentenyl adenine (2iP). The rooted plants were successfully acclimatized in the greenhouse with 100% survival rate. Inter-simple sequence repeats (ISSR) markers were used to assess the genetic fidelity of in vitro raised plants and the mother plant. It was revealed that monomorphic bands showing the absence of polymorphism in all in vitro raised plantlets analyzed, confirming the genetic uniformity among the regenerants. Phytochemical analysis was done to compare the antioxidant activities and HPLC fingerprinting assay of 80% aqueous ethanol extract of the leaves and stem of in vitro and in vivo grown C. obcordata. The extracts of the plants were examined for their antioxidant activities by using free radical 1, 1-diphenyl-2-picryl hydrazyl (DPPH) scavenging method, 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging ability, reducing power capacity, estimation of total phenolic content, flavonoid content and flavonol content. A simplified method for the detection of ascorbic acid, phenolic acids and flavonoids content was also developed by using reversed phase high-performance liquid chromatography (HPLC). This is the first report on the micropropagation, genetic integrity study and quantitative phytochemical analysis of in vitro regenerated plants of C. obcordata.Keywords: Cephalantheropsis obcordata, genetic fidelity, ISSR markers, HPLC
Procedia PDF Downloads 1561348 Loading Methodology for a Capacity Constrained Job-Shop
Authors: Viraj Tyagi, Ajai Jain, P. K. Jain, Aarushi Jain
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This paper presents a genetic algorithm based loading methodology for a capacity constrained job-shop with the consideration of alternative process plans for each part to be produced. Performance analysis of the proposed methodology is carried out for two case studies by considering two different manufacturing scenarios. Results obtained indicate that the methodology is quite effective in improving the shop load balance, and hence, it can be included in the frameworks of manufacturing planning systems of job-shop oriented industries.Keywords: manufacturing planning, loading, genetic algorithm, job shop
Procedia PDF Downloads 2951347 Unlocking the Genetic Code: Exploring the Potential of DNA Barcoding for Biodiversity Assessment
Authors: Mohammed Ahmed Ahmed Odah
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DNA barcoding is a crucial method for assessing and monitoring species diversity amidst escalating threats to global biodiversity. The author explores DNA barcoding's potential as a robust and reliable tool for biodiversity assessment. It begins with a comprehensive review of existing literature, delving into the theoretical foundations, methodologies and applications of DNA barcoding. The suitability of various DNA regions, like the COI gene, as universal barcodes is extensively investigated. Additionally, the advantages and limitations of different DNA sequencing technologies and bioinformatics tools are evaluated within the context of DNA barcoding. To evaluate the efficacy of DNA barcoding, diverse ecosystems, including terrestrial, freshwater and marine habitats, are sampled. Extracted DNA from collected specimens undergoes amplification and sequencing of the target barcode region. Comparison of the obtained DNA sequences with reference databases allows for the identification and classification of the sampled organisms. Findings demonstrate that DNA barcoding accurately identifies species, even in cases where morphological identification proves challenging. Moreover, it sheds light on cryptic and endangered species, aiding conservation efforts. The author also investigates patterns of genetic diversity and evolutionary relationships among different taxa through the analysis of genetic data. This research contributes to the growing knowledge of DNA barcoding and its applicability for biodiversity assessment. The advantages of this approach, such as speed, accuracy and cost-effectiveness, are highlighted, along with areas for improvement. By unlocking the genetic code, DNA barcoding enhances our understanding of biodiversity, supports conservation initiatives and informs evidence-based decision-making for the sustainable management of ecosystems.Keywords: DNA barcoding, biodiversity assessment, genetic code, species identification, taxonomic resolution, next-generation sequencing
Procedia PDF Downloads 231346 Neural Networks and Genetic Algorithms Approach for Word Correction and Prediction
Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga
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Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.Keywords: genetic algorithm, neural networks, word prediction, machine learning
Procedia PDF Downloads 1931345 Improving the Genetic Diversity of Soybean Seeds and Tolerance to Drought Irradiated with Gamma Rays
Authors: Aminah Muchdar
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To increase the genetic diversity of soybean in order to adapt to agroecology in Indonesia conducted ways including introduction, cross, mutation and genetic transformation. The purpose of this research is to obtain early maturity soybean mutant lines, large seed tolerant to drought with high yield potential. This study consisted of two stages: the first is sensitivity of gamma rays carried out in the Laboratory BATAN. The genetic variety used is Anjasmoro. The method seeds irradiated with gamma rays at a rate of activity with the old ci 1046.16976 irradiation 0-71 minutes. Irradiation doses of 0, 100, 200, 300, 400, 500, 600, 700, 800, 900 and 1000gy. The results indicated all seeds irradiated with doses of 0 - 1000gy, just a dose of 200 and 300gy are able to show the percentage of germination, plant height, number of leaves, number of normal sprouts and green leaves of the best and can be continued for a second trial in order to assemble and to get mutants which is expected. The result of second stage of soybean M2 Population irradiated with diversity Gamma Irradiation performed that in the form of soybean planting, the seed planted is the first derivative of the M2 irradiated seeds. The result after the age of 30ADP has already showing growth and development of plants that vary when compared to its parent, both in terms of plant height, number of leaves, leaf shape and leaf forage level. In the generative phase, a plant that has been irradiated 200 and 300 gy seen some plants flower form packs, but not formed pods, there is also a form packs of flowers, but few pods produce soybean morphological characters such as plant height, number of branches, pods, days to flowering, harvesting, seed weight and seed number.Keywords: gamma ray, genetic mutation, irradiation, soybean
Procedia PDF Downloads 3991344 Identification Strategies for Unknown Victims from Mass Disasters and Unknown Perpetrators from Violent Crime or Terrorist Attacks
Authors: Michael Josef Schwerer
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Background: The identification of unknown victims from mass disasters, violent crimes, or terrorist attacks is frequently facilitated through information from missing persons lists, portrait photos, old or recent pictures showing unique characteristics of a person such as scars or tattoos, or simply reference samples from blood relatives for DNA analysis. In contrast, the identification or at least the characterization of an unknown perpetrator from criminal or terrorist actions remains challenging, particularly in the absence of material or data for comparison, such as fingerprints, which had been previously stored in criminal records. In scenarios that result in high levels of destruction of the perpetrator’s corpse, for instance, blast or fire events, the chance for a positive identification using standard techniques is further impaired. Objectives: This study shows the forensic genetic procedures in the Legal Medicine Service of the German Air Force for the identification of unknown individuals, including such cases in which reference samples are not available. Scenarios requiring such efforts predominantly involve aircraft crash investigations, which are routinely carried out by the German Air Force Centre of Aerospace Medicine as one of the Institution’s essential missions. Further, casework by military police or military intelligence is supported based on administrative cooperation. In the talk, data from study projects, as well as examples from real casework, will be demonstrated and discussed with the audience. Methods: Forensic genetic identification in our laboratories involves the analysis of Short Tandem Repeats and Single Nucleotide Polymorphisms in nuclear DNA along with mitochondrial DNA haplotyping. Extended DNA analysis involves phenotypic markers for skin, hair, and eye color together with the investigation of a person’s biogeographic ancestry. Assessment of the biological age of an individual employs CpG-island methylation analysis using bisulfite-converted DNA. Forensic Investigative Genealogy assessment allows the detection of an unknown person’s blood relatives in reference databases. Technically, end-point-PCR, real-time PCR, capillary electrophoresis, pyrosequencing as well as next generation sequencing using flow-cell-based and chip-based systems are used. Results and Discussion: Optimization of DNA extraction from various sources, including difficult matrixes like formalin-fixed, paraffin-embedded tissues, degraded specimens from decomposed bodies or from decedents exposed to blast or fire events, provides soil for successful PCR amplification and subsequent genetic profiling. For cases with extremely low yields of extracted DNA, whole genome preamplification protocols are successfully used, particularly regarding genetic phenotyping. Improved primer design for CpG-methylation analysis, together with validated sampling strategies for the analyzed substrates from, e.g., lymphocyte-rich organs, allows successful biological age estimation even in bodies with highly degraded tissue material. Conclusions: Successful identification of unknown individuals or at least their phenotypic characterization using pigmentation markers together with age-informative methylation profiles, possibly supplemented by family tree search employing Forensic Investigative Genealogy, can be provided in specialized laboratories. However, standard laboratory procedures must be adapted to work with difficult and highly degraded sample materials.Keywords: identification, forensic genetics, phenotypic markers, CPG methylation, biological age estimation, forensic investigative genealogy
Procedia PDF Downloads 461343 A Matheuristic Algorithm for the School Bus Routing Problem
Authors: Cagri Memis, Muzaffer Kapanoglu
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The school bus routing problem (SBRP) is a variant of the Vehicle Routing Problem (VRP) classified as a location-allocation-routing problem. In this study, the SBRP is decomposed into two sub-problems: (1) bus route generation and (2) bus stop selection to solve large instances of the SBRP in reasonable computational times. To solve the first sub-problem, we propose a genetic algorithm to generate bus routes. Once the routes have been fixed, a sub-problem remains of allocating students to stops considering the capacity of the buses and the walkability constraints of the students. While the exact method solves small-scale problems, treating large-scale problems with the exact method becomes complex due to computational problems, a deficiency that the genetic algorithm can overcome. Results obtained from the proposed approach on 150 instances up to 250 stops show that the matheuristic algorithm provides better solutions in reasonable computational times with respect to benchmark algorithms.Keywords: genetic algorithm, matheuristic, school bus routing problem, vehicle routing problem
Procedia PDF Downloads 701342 Air Quality Forecast Based on Principal Component Analysis-Genetic Algorithm and Back Propagation Model
Authors: Bin Mu, Site Li, Shijin Yuan
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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model
Procedia PDF Downloads 2241341 A Genetic Algorithm Based Permutation and Non-Permutation Scheduling Heuristics for Finite Capacity Material Requirement Planning Problem
Authors: Watchara Songserm, Teeradej Wuttipornpun
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This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.Keywords: capacitated MRP, genetic algorithm, linear programming, automotive industries, flow shop, application in industry
Procedia PDF Downloads 4881340 Optimization of Wavy Channel Using Genetic Algorithm
Authors: Yue-Tzu Yang, Peng-Jen Chen
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The present study deals with the numerical optimization of wavy channel with the help of genetic algorithm (GA). Three design variables related to the wave amplitude (A), the wavelength (λ) and the channel aspect ratio (α) are chosen and their ranges are decided through preliminary calculations of three-dimensional Navier-stokes and energy equations. A parametric study is also performed to show the effects of different design variables on the overall performance of the wavy channel. Objective functions related to the heat transfer and pressure drop, performance factor (PF) is formulated to analyze the performance of the wavy channel. The numerical results show that the wave amplitude and the channel aspect ratio have significant effects on the thermal performance. It can improve the performance of the wavy channels by increasing wave amplitude or decreasing the channel aspect ratio. Increasing wavelengths have no significant effects on the heat transfer performance.Keywords: wavy channel, genetic algorithm, optimization, numerical simulation
Procedia PDF Downloads 2961339 Assessment of Memetic and Genetic Algorithm for a Flexible Integrated Logistics Network
Authors: E. Behmanesh, J. Pannek
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The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.Keywords: integrated logistics network, flexible path, memetic algorithm, genetic algorithm
Procedia PDF Downloads 3731338 Transformer Design Optimization Using Artificial Intelligence Techniques
Authors: Zakir Husain
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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)
Procedia PDF Downloads 5811337 Material Parameter Identification of Modified AbdelKarim-Ohno Model
Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek
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The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting
Procedia PDF Downloads 451