Genethic algorithm

According to different needs of users, there are different consumption habits. Consumption habits of people, which have the same age group or the same professions, are similar. A type of internet usage habits of people in this way is one of these habits. In recent years, developments in technology, GSM, and especially with 4G mobile internet usage have found applications in many areas of daily life. Enter to internet, wherever users need to, creates freedom. Messaging, media, finance and many different needs can be met through this connection. Users' occupation, age, gender, location, usage patterns according to different characteristics such as income level and the relevant properties are similar to each other according to the amount of internet usage (in Mb Download) connected to internet and internet usage frequency and duration of exposure can be clustered. SOM type of study, personal internet usage by artificial neural networks (data of the CDR) process and their profession, age, gender, location is to cluster usage patterns according to the values.

According to different needs of users, there are different consumption habits. Consumption habits of people, which have the same age group or the same professions, are similar. A type of internet usage habits of people in this way is one of these habits. In recent years, developments in technology, GSM, and especially with 4G mobile internet usage have found applications in many areas of daily life. Enter to internet, wherever users need to, creates freedom. Messaging, media, finance and many different needs can be met through this connection. Users' occupation, age, gender, location, usage patterns according to different characteristics such as income level and the relevant properties are similar to each other according to the amount of internet usage (in Mb Download) connected to internet and internet usage frequency and duration of exposure can be clustered. SOM type of study, personal internet usage by artificial neural networks (data of the CDR) process and their profession, age, gender, location is to cluster usage patterns according to the values.

In this paper a method for generating Oriented Bounding Boxes (OBB) using genetic algorithms (GA) is proposed. OBBs are used in a hierarchy of bounding volumes to detect collisions between objects. Currently, the most used method for generating OBBs is based on the covariance matrix (CV) of the points of the model, but it has many flaws and in most cases does not find the optimum OBB. We performed several tests with both methods (CV vs. GA). Generally the GA method provides a better adjustment of the OBB to the geometry of the models than the CV method. The metric used for measuring the adjustment of the OBB was the volume of the OBB. The time required for performing the collision detection was also tested, obtaining better results with the GA method. It is suggested to use the GA method when the models are rigid and will not be deformed.

Resumen Se implementó un algoritmo para construir árboles de Partición Binaria del Espacio (BSP) basado en algoritmos genéticos. Los métodos tradicionales de construcción de árboles BSP, limitan la búsqueda a planos obtenidos a través de los polígonos de la ...

In this paper, a new simulation model to analyze congestions in ship evacuation is introduced. To guarantee a safe evacuation, the model considers the most important reallife factors including, but not limited to, the passengers' panic, the age or sex of the passengers, the structure of the ship. The qualitative factors have been quantized in order to compute the probability of congestion during the entire evacuation. We then utilize the dynamic Bayesian network (DBN) to predict congestion and to handle the non-stationarity of the scenario with respect to the time. Considering the worst-case scenarios and running the simulation for two groups of passengers (different in sex, age, and physical ability), we demonstrate the distinct effects of these groups on the congestion. The role of decision supports (DS), such as evacuation applications and rescue team presence is also studied. In addition, the impact of congested escape routes on the evacuation time is investigated. The results of this paper are of great importance for maritime organizations, emergency management sectors, and rescuers onboard the ships, which try to alleviate the human or property losses.

In this paper, the implementation of matrix multiplication using FPGA-Based computing platform is investigated. Because the highly parallel nature of matrix multiplication it makes an ideal application for using such platform. The computations are done in parallel by multipliers and adders, which are implemented on multiple FPGA boards. The major challenge of this task is I/O interfaces between PC and FPGA board. In our approach, we adopt the software/hardware codesign to exploit the highly parallel nature of operations, which cannot be exploited in our purely software implementation. Our matrix multiplier is modeled in VHDL and runs on an ARC-PCI FPGA board. The purpose of the software part of our codesign system is to provide I/O to the hardware. This part is implemented on a PC with a C program and a device driver to communicate with the board. We present the performance comparison of our codesign and purely software implementation, as well as the performance comparison of existi...

El presente artículo de investigación tiene como objetivo utilizar algoritmo genético generacional, propio de la inteligencia artificial, donde se aprovecha el proceso evolutivo para optimizar el recorrido de los n puntos o nodos, a un coste de computador menor. Una de las ventajas de este método evolutivo es que no compiten todos contra todos, sino que se crea y procesa una porción de la población total, con el objetivo de encontrar la posible mejor ruta, o también llamada búsqueda local. Se ha considerado para el método de la ruleta, cruce por intercambio de 2 puntos, mutación por intercambio y método de parada de acuerdo a la cantidad de generaciones. En un computador de regular característica se logró implementar el algoritmo genético generacional en lenguaje Matlab 8.3, tomando como ejemplo las distancias de cada ciudad. Se obtuvieron como resultados para n puntos o nodos, en cada evaluación, las posibles mejores rutas basándose en el modelo evolutivo. Las pruebas realizadas desde 100 hasta 1000 ciudades resultaron en tiempos de 3,2006 s y 27,924 s, respectivamente. De acuerdo al conjunto de pruebas, demuestra un incremento de manera polinómica de nivel 2; por lo que esta investigación se centra en el incremento de los dos métodos de parada a una secuencia lineal.

Kebutuhan akan kendaraan dapat dibilang sebagai salah satu kunci dari berjalannya ekonomi dunia. Akan tetapi, efisiensi desain spesifikasi kendaraan masih menjadi topik hangat di kalangan desainer otomotif. Hal ini karena meskipun ada jutaan kendaraan di seluruh dunia, tidak semua desain kendaraan dapat menunjukkan performa yang optimal di segala keadaan. Aspek spesifikasi kendaraan yang memiliki pengaruh paling besar antara lain daya mesin, ukuran ban, dan berat kendaraan. Oleh karena itu, dibutuhkan suatu optimasi desain spesifikasi kendaraan yang hanya membutuhkan faktor ukuran ban dan berat kendaraan, di mana berat kendaraan tersebut dapat direpresentasikan oleh dua faktor besar, yaitu kapasitas kargo dan kapasitas bahan bakar. Dalam penelitian ini ditelusuri kemungkinan optimasi spesifikasi truk sampah berdasarkan faktor-faktor tersebut dalam tujuannya mengumpulkan sampah dan kembali ke sentra pengumpulan sampah tanpa kehabisan bahan bakar menggunakan aplikasi Trash Queen. Tras...

Image Registration is the process of determining a transform that provides the most accurate match between two images. The search for matching transformation can be automated with the use of suitable metric, but it is difficult to determine local maxima with direct search methods. In this paper a simple and powerful search strategy based on genetic algorithm is proposed to register satellite images. This method applies mutual information (MI) to measure statistical dependence of information redundancy between the image intensities of corresponding voxels in both floating image and reference image. Partial Volume distribution interpolation (PV) is used to compute the MI criterion. Scope of the paper is limited to pair of images, which are misaligned by rigid transformation (i.e. rotation and/or translation). Performance of genetic algorithm based proposed approach is compared with existing search methods, which shows that the proposed approach overcomes the limitation of local maxima...

This research is related to the route of picking up the waste which done by janitors in housing complex of Aur Duri Indah Rt.14 Jambi considering the condition of that housing which have some crossroads, such that janitors take the same road twice which seems inefficient in terms of time and fuel consumption. This research is aimed to identify scientifically about the shortest and more efficient route which should be taken by janitors. This problem is considered as optimization problem through graph modelling. To check the efficient route, the existence of Hamiltonian Path of the graph is identified by using Depth-First Search method, and so is the shortest path. It is found that there are 39 Hamiltonian paths and the shortest path has total distance of 793.8 meter. By the existence of the shortest Hamiltonian Path, it is confirmed that janitors in housing complex of Aur Duri Indah Rt.14 can travel each road once with total distance is about 793.8 meter.

Kebutuhan akan kendaraan dapat dibilang sebagai salah satu kunci dari berjalannya ekonomi dunia. Akan tetapi, efisiensi desain spesifikasi kendaraan masih menjadi topik hangat di kalangan desainer otomotif. Hal ini karena meskipun ada jutaan kendaraan di seluruh dunia, tidak semua desain kendaraan dapat menunjukkan performa yang optimal di segala keadaan. Aspek spesifikasi kendaraan yang memiliki pengaruh paling besar antara lain daya mesin, ukuran ban, dan berat kendaraan. Oleh karena itu, dibutuhkan suatu optimasi desain spesifikasi kendaraan yang hanya membutuhkan faktor ukuran ban dan berat kendaraan, di mana berat kendaraan tersebut dapat direpresentasikan oleh dua faktor besar, yaitu kapasitas kargo dan kapasitas bahan bakar. Dalam penelitian ini ditelusuri kemungkinan optimasi spesifikasi truk sampah berdasarkan faktor-faktor tersebut dalam tujuannya mengumpulkan sampah dan kembali ke sentra pengumpulan sampah tanpa kehabisan bahan bakar menggunakan aplikasi Trash Queen. Tras...

Travelling Salesman Problem (TSP) is the problem for finding the shortest route starting from start node then visiting number of nodes exactly once and finally go back to start node. If a TSP has a lot of nodes, it will be a NP-Hard Problem. Algorithms working based on heuristic and metaheuristic can be a solution for solving NP-Hard Problem. Savings Algorithm is a heuristic algorithm, so it’s solution may be not the best solution, therefore there is a chance to improve it. Genetic Algorithm is a metaheuristic that can be applied on many optimization problems, including TSP. This paper will discuss about GA for improving route TSP generated by Savings Algorithm. On testing of 10 instances, showing that algorithm based on GA can improve route of TSP generated by Savings Algorithm.

In everyday life we ​​often travel from place to place. So that we need to consider the time and cost efficient. Therefore, accuracy is needed to determine the shortest path as a consideration in decision to show the path to be taken. The results obtained also require speed and accuracy with the help of a computer. Using or functioning a computer there must be a distributed program in it. The programs contained in the computer vary widely and each program must use an algorithm. Algorithm is a collection of commands to solve a problem gradually from start to finish. There are various algorithms that can be used to find the shortest route such as Breadth First Search algorithm, Depth First Search, A *, Hill Climbing and others. For that required comparison algorithm which is able to find the shortest route accurately and efficiently. In this journal, the algorithm to be compared is the genetic algorithm and greedy algorithm to find the shortest route on a map. Some aspects to be compa...

Tempat sampah tidak dapat diperkirakan kapan penuh atau kosong, mengakibatkan petugas dalam pengangkutannya sering mengunjungi tempat sampah yang kosong dan terkadang petugas sering kembali ke tempat yang kosong tersebut. Tempat sampah yang ada di daerah Perumahan Buah Batu (PBB) merupakan tempat sampah yang dibuat di depan rumah dengan bentuk kubus berdiameter sekitar 60cm x 60cm disertai penutup tempat sampah. Dari permasalahan tersebut dibutuhkan smart monitoring yang dapat menunjukan tempat sampah yang isinya dapat diangkut oleh petugas. Sistem monitoring ini menggunakan sensor ultrasonik dengan output nilai ketinggian sampah dan sensor loadcell dengan ouput nilai berat sampah, dimana nilai output sensor merupakan nilai input untuk Fuzzy, setelah sistem diteruskan dengan sistem Dijkstra. Fuzzy menghasilkan nilai keputusan dari output sensor, hasil fuzzy menjadi penentu tempat sampah mana yang diangkut, jika hasil fuzzy lebih dari satu tempat sampah berstatus ‘Angkut’ dengan nila...

The increasing population growth and rapid urbanization have resulted in large amounts of solid municipal waste (SMW). Nowadays, the problem of waste management is a problem that is being experienced by every country in the world. As a result, implementing efficient waste management strategies is increasingly needed. The collection and transportation of solid waste is the most important thing to pay attention to in waste management efficiency to reduce the costs of collecting and transporting solid waste. The research started by collecting data and interviewing the environmental services of Semarang City about the waste transportation system in Semarang City. The results of the data and interviews will then be used as a reference for the system analysis to be made. Then proceed with designing information systems. After that, the information system was developed by applying the Traveling Salesman Problem (TSP) method using a heuristic in the form of K-means Clustering. With the help ...

Land transport like buses and public transportation is becoming a tool in the dibtuhkan transportation to tourist sites. Solo is one of the most visited tourist attractions where travelers who want to spend a lot of time for play, recreation, or for science in the city solo. However, information about transportation is less visible, and even the manual nature of the process information. Therefore we need a method to solve problems in the field of transport, which will be searched in the search for the closest distance transport journey from the initial position to tourism in the town of Surakarta. Genetic algorithms can be implemented for searching transit lines to attractions in the city of Surakarta. This is expected to help in the journey to the attraction in order to be faster if you know the closest point so that it can minimize the distance from one attraction to another attraction. This study yielded information such as street names as Surakarta travel route, transit lines, the travel distance and total travel animation from the initial position to the departure to the tourist sites. Based on the test results shows that Genetic algorithms can produce close to transport routes are the closest results in the case of the determination of the town of Surakarta tourism transport compared with the results from google maps route vehicles.

In this paper a method for generating Oriented Bounding Boxes (OBB) using genetic algorithms (GA) is proposed. OBBs are used in a hierarchy of bounding volumes to detect collisions between objects. Currently, the most used method for generating OBBs is based on the covariance matrix (CV) of the points of the model, but it has many flaws and in most cases does not find the optimum OBB. We performed several tests with both methods (CV vs. GA). Generally the GA method provides a better adjustment of the OBB to the geometry of the models than the CV method. The metric used for measuring the adjustment of the OBB was the volume of the OBB. The time required for performing the collision detection was also tested, obtaining better results with the GA method. It is suggested to use the GA method when the models are rigid and will not be deformed.

Waste is one of the problems faced by Bogor city, with waste production of 2,701 m3 per day. Waste management of Bogor city currently still has limited garbage facilities and infrastructure that make garbage not yet maximally resolved, including not having a regular schedule of truck distribution in serving sub-district waste. The aim of this research is to optimize the distribution of garbage transport trucks using genetic algorithms. The initial stage of the research carried out is the calculation of the waste generation projection based on population data from Badan Pusat Statistik with reference to SNI 19-3964-1994. Optimization with genetic algorithms consists of a selection process where this study uses the Roulette Wheel selection method, crossover,  and mutation. The optimization process using genetic algorithms (GA) from the number of DLH trucks operating currently as many as 60 trucks in serving 490 polling stations (TPS) spread across six sub-districts in Bogor City, the ...

Aktivitas manusia dalam memenuhi kebutuhan tidak bisa dihindari dengan selalu menghasilkan sampah. Timbunan sampah yang terus menerus akan menyebabkan jejak karbon. Salah satu penyumbang timbunan sampah adalah aktivitas akademik. Universitas Ma Chung merupakan salah satu lembaga pendidikan di kota Malang. Universitas Ma Chung belum menjadi salah satu eco campus di Indonesia. Hal tersebut dapat diketahui dari pengelolaan sampah yang ada di Universitas Ma Chung. Oleh sebab itu diusulkan beberapa skenario yang dapat mengurangi jumlah sampah. Melakukan perhitungan menggunakan Stella untuk simulasi peningkatan jumlah sampah yang dihasilkan menggunakan metode Sistem Dinamis. Hasil perhitungan menunjukkan bahwa skenario usulan mengenai adanya air siap minum, untuk memenuhi kebutuhan air mineral sivitas akademik menurunkan jumlah sampah sekitar 945 kg untuk satu tahun ke depan dari kondisi awal. Hal tersebut menunjukkan bahwa skenario pertama sangat optimal karena dapat memenuhi kebutuhan k...

Penulisan artikel ini membahas mengenai penerapan Algoritma Tabu Search pada model ACVRP untuk mencari rute pengangkutan sampah yang optimal di Kecamatan Kalidoni. ACVRP merupakan matriks jarak asimetris dimana perjalanan dari tempat i ke j tidak sama dengan perjalanan dari tempat j ke i. Proses algoritma berpindah dari satu solusi ke solusi berikutnya dengan memilih solusi terbaik yang ada pada Tabu List. Hasil penelitian menunjukkan bahwa rute terpendek yang diperoleh dari perhitungan menggunakan Algoritma Tabu yaitu berjarak 17,7 km pada iterasi 1, dengan rute (6 – 4 – 5 – 3 – 2 – 1 – 0) yaitu TPS 6 (Jl. Mayor Zen Mata Merah (Depan SMA N 7)) – TPS 4 (Jl. Arozak (Depan Halte Sekojo)) – TPS 5 (Jl. Arozak (Depan SPBU Sekojo)) – TPS 3 (Jl. Arozak (Depan Perumahan Buana Hijau)) – TPS 2 (Jl. Arozak (Depan Perumahan Kedamaian)) – TPA Sukawinatan.

In this paper a method for generating Oriented Bounding Boxes (OBB) using genetic algorithms (GA) is proposed. OBBs are used in a hierarchy of bounding volumes to detect collisions between objects. Currently, the most used method for generating OBBs is based on the covariance matrix (CV) of the points of the model, but it has many flaws and in most cases does not find the optimum OBB. We performed several tests with both methods (CV vs. GA). Generally the GA method provides a better adjustment of the OBB to the geometry of the models than the CV method. The metric used for measuring the adjustment of the OBB was the volume of the OBB. The time required for performing the collision detection was also tested, obtaining better results with the GA method. It is suggested to use the GA method when the models are rigid and will not be deformed.

Image Registration is the process of determining a transform that provides the most accurate match between two images. The search for matching transformation can be automated with the use of suitable metric, but it is difficult to determine local maxima with direct search methods. In this paper a simple and powerful search strategy based on genetic algorithm is proposed to register satellite images. This method applies mutual information (MI) to measure statistical dependence of information redundancy between the image intensities of corresponding voxels in both floating image and reference image. Partial Volume distribution interpolation (PV) is used to compute the MI criterion. Scope of the paper is limited to pair of images, which are misaligned by rigid transformation (i.e. rotation and/or translation). Performance of genetic algorithm based proposed approach is compared with existing search methods, which shows that the proposed approach overcomes the limitation of local maxima...

Vehicle Routing Problem (VRP) merupakan suatu permasalahan yang berkaitan dengan bagaimana menentukan rute yang dianggap optimal dan melibatkan lebih dari satu alat angkut demi memperhatikan beberapa kendala dalam melayani sejumlah tempat layanan sesuai dengan permintaan. Salah satu varian dari VRP adalah capacitated vehicle routing problem with time window (CVRPTW) varian ini menambahkan kendala kapasitas alat angkut sebagai salah satu pertimbangan didalam mengangkut ke masing masing tujuan dan kemudian memberikan jendela waktu didalam proses pengangkutannya. Tujuan dari penulisan ini adalah menjelaskan pembentukan model dari CVRPTW untuk permasalahan rute pengangkutan sampah dari tiap rumah Sampai Ke Tempat Pembuangan Akhir, dengan pertimbangan waktu yang tersedia dan kapasitas angkut alat angkut yang tersedia, Sedangkan Penyelesaiannya yaitu dengan menggunakan pendekatan algoritma sweep. Algoritma Ini merupakan algoritma yang terdiri dari dua tahap, pada tahapan pertama yaitu clu...

Kota Bandung mengalami peningkatan jumlah timbunan sampah.Sementara kegiatan pengangkutan sampah khususnya kendaraan angkutan sampah belum digunakan secara optimal.Kota Bandung Wilayah Timur memiliki 48 TPS atau bak sampah yang tersebar.Rute pengangkutan sampah dibuat dengan memperhatikan keterbatasan seperti kapasitas angkut kendaraan. Kondisi pengangkutan sampah dianalogikan dengan model Open Vehicle Routing Problem, yakni setiap kendaraan tidak wajib kembali ke depot atau kendaraan dapat berhenti disalah satu pelanggan. Model penelitian ini disebut Capasitated with Open Vehicle Routing Problem (COVRP) dengan tujuan meminimasi biaya transportasi.Permasalahan COVRP ini dapat diselesaikan dengan metode metaheuristik seperti algoritma genetika, dengan populasi awal menggunakan algoritma heuristik seperti saving heuristic.Hasil dari metode saving heuristic ini terbentuk 13 tur pengangkutan sampah yang tersebar di wilayah Bandung timur yang selanjutnya di integrasikan menggunakan pendekatan algoritma genetika.Hasil penelitian ini menunjukkan bahwa algoritma genetika dapat meminimalkan jarak tempuh pengangkutan sampah dan biaya transportasi. Dimana penurunan total jarak tempuh sebesar 7,1 % dan penurunan total biaya transportasi sebesar 6,49 %.

The transportation network design problem is a well-known optimization problem with many practical applications. This paper deals with demand-based applications, where the operational as well as many other decisions are often made under uncertainty. Capturing the uncertain demand by using scenario-based approach, we formulate the two-stage stochastic mixed-integer linear problem, where the decision, which is made under uncertainty, of the first-stage program, is followed by the second-stage decision that reacts to the observed demand. Such a program may reach solvability limitations of algorithms for large scale real world data, so we refer to the so-called hybrid algorithm that combines a traditional optimization algorithm and a suitable genetic algorithm. The obtained results are presented in an explanatory form with the use of a sequence of figures.

Waste is one of the problems faced by Bogor city, with waste production of 2,701 m3 per day. Waste management of Bogor city currently still has limited garbage facilities and infrastructure that make garbage not yet maximally resolved, including not having a regular schedule of truck distribution in serving sub-district waste. The aim of this research is to optimize the distribution of garbage transport trucks using genetic algorithms. The initial stage of the research carried out is the calculation of the waste generation projection based on population data from Badan Pusat Statistik with reference to SNI 19-3964-1994. Optimization with genetic algorithms consists of a selection process where this study uses the Roulette Wheel selection method, crossover,  and mutation. The optimization process using genetic algorithms (GA) from the number of DLH trucks operating currently as many as 60 trucks in serving 490 polling stations (TPS) spread across six sub-districts in Bogor City, the ...

With the development of Internet and network technology, Ubiquitous computing is widely enabled. Ubiquitous environment is confronted with many unique challenges. Au-thentication, Authorization and Accounting (AAA) is one of the most challenging security problems in ubiquitous environment due to its feature of providing anytime anywhere services. Existing authentication schemes aim at only entry-point au-thentication, which may not suite the dynamic Ubiquitous environment. We propose an authentication scheme which is based on user context information. Whenever a user moves into Ubiquitous service environment, system at first, collects the context and provides the best unique User Certificate to access the preliminary services. For quick and fast context evaluation, we apply genetic algorithm for the context selection, trust evaluation and credential verification of authenticated user. The designed authentication has been tested in a ubiquitous museum environment. The results are qui...

In commercial poultry production there are a number of diseases which are of particular importance due to the heavy economic losses that can arise if a flock becomes infected. The development of an automated and rapid disease detection system would therefore be of considerable benefit to both production and animal welfare. This study represents an intelligence device for diagnosing avian diseases by using Data-mining methods and Dempster-Shafer evidence theory (D-S). 14-day-old chickens were divided into four groups. Each group was deliberately infected with a disease: Newcastle Disease (ND), Bronchitis Virus (BV), Avian Influenenza (AI), and the last group was considered as control samples. Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) were used to process the chicken's sound signals in frequency and time-frequency domains, respectively. In order to achieve information, 25 statistical features from frequency domains, and 75 statistical features from time-frequency domains were extracted. During dimensionality reduction stage, the best features of the sound signals were selected, using improved distance evaluation (IDE) method. The chicken's sound signals were analyzed in two consecutive days after virus infection. Support vector machine (SVM) was used as the classifier in this study. The first classification was done with SVM and based on sound features in frequency and time-frequency domains with accuracy of 41.35 and 83.33%, respectively. The accuracy of the method based on D-S infusion of sound data reached 91.15%. The developed model based on achievement result could diagnose Newcastle Disease, Bronchitis Virus and Avian Influenza from sound signals.

Association Rule Mining is one of the most well - liked techniques of data mining strategies whose primary aim is to extract associations among sets of items or products in transactional databases. However, mining association rules typically ends up in a really large amount of found rules, leaving the database analyst with the task to go through all the association rules and find out the interesting ones. Currently Apriori Algorithm plays an important role in deriving frequent itemsets and then extracting association rules out of it. However Apriori Algorithm uses Conjunctive nature of association rules, and single minimum support threshold to get the interesting rules. But these factors don't seem to be alone sufficient to extract interesting association rules effectively. Hence in this paper, we proposed a completely unique approach for optimizing association rules using Multi-objective feature of Genetic Algorithm with multiple quality measures i.e. support, confidence, compr...

The concept of PID controllers (proportional integral derivative) belongs to the most frequently used principles of controlling in industrial and non-industrial applications. The process of setting of PID controller can be determined as optimization task. Requiring optimal settings of PID controller we can specify more goals of optimization which are often contradictory. Optimal setting of PID controller is generally task of nonlinear mathematic optimization which is furthermore done on top of dynamic system. In this paper shall be shown multi-criterion optimization of PID controller setting of two systems using soft computing optimization method HC12. To be correct the solution shall be compared with classic method of nonlinear optimization based on Nelder- Mead method and also shall be shown solution of PID controller using classic methods Zigler Nichols and Modulus Optimum.

We present a new, fast approach for updating oriented bounding box hierarchies for articulated humanoid models, using a bottom up approach. The algorithm approximates existing techniques by assuming a major body axis. Existence of a major axis allows merging of bounding boxes in a hierarchy approximately but with sufficient accuracy. For scenarios with close proximity a speedup by a factor 2 on average is achieved compared to existing techniques.

The foremost objective of the present research project consists developing an Intelligent Robotic System (SIR for its name in Spanish, Sistema Inteligente Robótico) that solves an unknown jigsaw puzzle in a reduced amount of time. To fulfill the objective, SIR applies pattern recognition techniques as edge and feature detection in conjunction with Genetic Algorithms. Many authors have addressed the jigsaw puzzle problem. By comparing their work, the NP-Complete nature of the problem appeared as a common denominator on them. SIR relies on those experiences, results, conclusions and observations as a working base for a new approach to the problem. This approach involves a conversion of the puzzle model to a Graph Theory model. The study of this model plus the inclusion of a different analogy and solution approach is the main contribution of this work. It describes the theoretical and practical frameworks, current state of the project and future work.

With the development of Internet and network technology, Ubiquitous computing is widely enabled. Ubiquitous environment is confronted with many unique challenges. Authentication, Authorization and Accounting (AAA) is one of the most challenging security problems in ubiquitous environment due to its feature of providing anytime anywhere services. Existing authentication schemes aim at only entry-point authentication, which may not suite the dynamic Ubiquitous environment. We propose an authentication scheme which is based on user context information. Whenever a user moves into Ubiquitous service environment, system at first, collects the context and provides the best unique User Certificate to access the preliminary services. For quick and fast context evaluation, we apply genetic algorithm for the context selection, trust evaluation and credential verification of authenticated user. The designed authentication has been tested in a ubiquitous museum environment. The results are quite...

Image Registration is the process of determining a transform that provides the most accurate match between two images. The search for matching transformation can be automated with the use of suitable metric, but it is difficult to determine local maxima with direct search methods. In this paper a simple and powerful search strategy based on genetic algorithm is proposed to register satellite images. This method applies mutual information (MI) to measure statistical dependence of information redundancy between the image intensities of corresponding voxels in both floating image and reference image. Partial Volume distribution interpolation (PV) is used to compute the MI criterion. Scope of the paper is limited to pair of images, which are misaligned by rigid transformation (i.e. rotation and/or translation). Performance of genetic algorithm based proposed approach is compared with existing search methods, which shows that the proposed approach overcomes the limitation of local maxima...

Resumen La prueba basada en búsqueda permite generar casos de prueba automáticamente mediante la codificación de un criterio de cobertura como una función de aptitud que guía la búsqueda. Los algoritmos genéticos se han aplicado con éxito a este tipo de prueba utilizando principalmente criterios de cobertura estructural. Este trabajo presenta el análisis realizado para mejorar el comportamiento del generador de casos de prueba Rodan, que emplea un algoritmo genético para generar casos de prueba que matan mutantes producidos a partir de composiciones WS-BPEL. Se presentan los resultados obtenidos sobre un caso de estudio clásico en la literatura de prueba (un clasificador de triángulos) para tres operadores de mutación, con siembra y sin ella, y con distintos tamaños del espacio de búsqueda. Estos resultados se comparan con los obtenidos mediante generación aleatoria de casos de prueba.

Sexing is a difficult task for most birds (especially ornamental birds) involving expensive, state-of-the-art equipment and experiments. An intelligent fowl sexing system was developed based on data mining methods to distinguish hen from cock hatchlings. The vocalization of one-day-old hatchlings was captured by a microphone and a sound card. To obtain more accurate information from the recordings, time-domain sound signals were converted into the frequency domain and the time-frequency domain using Fourier transform and discrete wavelet transform, respectively. During data-mining from signals of these three domains, 25 statistical features were extracted. The Improved Distance Evaluation (IDE) method was used to select the best features and also to reduce the classifier's input dimensions. Fowls’ sound signals were classified by Support Vector Machine (SVM) with a Gaussian Radial Basis Function (GRBF). This classifier identified and classified cocks and hens based on the select...

Image Registration is the process of determining a transform that provides the most accurate match between two images. The search for matching transformation can be automated with the use of suitable metric, but it is difficult to determine local maxima with direct search methods. In this paper a simple and powerful search strategy based on genetic algorithm is proposed to register satellite images. This method applies mutual information (MI) to measure statistical dependence of information redundancy between the image intensities of corresponding voxels in both floating image and reference image. Partial Volume distribution interpolation (PV) is used to compute the MI criterion. Scope of the paper is limited to pair of images, which are misaligned by rigid transformation (i.e. rotation and/or translation). Performance of genetic algorithm based proposed approach is compared with existing search methods, which shows that the proposed approach overcomes the limitation of local maxima...

FlexRay is getting popular among car makers to be used as a communication backbone for in-vehicle networking systems. It serves both time-triggered as well as event-triggered applications by maintaining static and dynamic segments in its communication cycle. There are many works on the scheduling of the signals that are motivated by different vehicular applications. In this survey the focus is on the scheduling and optimization of the static segment of the FlexRay protocol that supports periodic tasks. Various approaches and their properties are reviewed including bin packing, genetic algorithm, linear integer programming, non-linear integer programming, mixedlinear integer programming as well as the constraint programming algorithms.

We present a new, fast approach for updating oriented bounding box hierarchies for articulated humanoid models, using a bottom up approach. The algorithm approximates existing techniques by assuming a major body axis. Existence of a major axis allows merging of bounding boxes in a hierarchy approximately but with sufficient accuracy. For scenarios with close proximity a speedup by a factor 2 on average is achieved compared to existing techniques.

We present a new, fast approach for updating oriented bounding box hierarchies for articulated humanoid models, using a bottom up approach. The algorithm approximates existing techniques by assuming a major body axis. Existence of a major axis allows merging of bounding boxes in a hierarchy approximately but with sufficient accuracy. For scenarios with close proximity a speedup by a factor 2 on average is achieved compared to existing techniques.

 Abstract— Function Approximation is a popular engineering method used in system identification or equation optimization. Artificial Intelligence (AI) techniques have been used extensively to spot the best curves that match the real behavior of the system due to the wide spectrum of the search space. Genetic algorithm is well-known for its fast convergence and ability to find an optimal structure of the solution. In this paper, we propose using a genetic algorithm method as a function approximator to get a correlation for seawater density. We will use a polynomial form of the approximation. After implementing the algorithm, the results from the produced function are compared with the real data used in the algorithm.

The main purpose of the paper is to present a specific case of dynamic pricing for the newsvendor problem. Firstly, a short overview of the newsvendor problem is given together with references to selected literature and remarks to its applicability. Then, dynamic pricing principles are discussed together with references to a decision dependent randomness case in stochastic programming. The dynamic pricing problem deals with determination of selling prices over time for a product whose demand is random and whose supply is fixed. We approach this problem by formulating the newsvendor problem, which is introduced as a single period problem in our case. We focus on specific features of the demand function assuming a decision dependent uniform distribution. We assume that its support size linearly decreases with the increase of the price. Under such assumptions, the model has suitable computational features related to the expectation of the objective function. In addition, a possibility to increase the profit by change of the price may appear. The model formulation allows us to use the MAPLE software for symbolic computations and visualization of results. The test results for the selected data set are visualized at the end of the paper.

An algorithm to construct Binary Space Partition (BSP) trees based on genetic algorithms was implemented. Traditional methods for constructing BSP trees limit the search to planes obtained from the scene polygons, or parallel to the planes x=0, y=0 or z=0. In our case, to find each partition plane, the genetic algorithm is executed to find the plane’s coefficients, without additional restrictions. Time measures were taken with scenes from the Quake III game, and scenes created with Lightwave, that demonstrated on practice that the results obtained using genetic algorithms are superiors than using traditional methods, with an acceptable response time. Se implementó un algoritmo para construir árboles de Partición Binaria del Espacio (BSP) basado en algoritmos genéticos. Los métodos tradicionales de construcción de árboles BSP, limitan la búsqueda a planos obtenidos a través de los polígonos de la escena, o paralelos a los planos x=0, y=0 o z=0. En nuestro caso, para hallar cada plano...

The objective of this work is to propose two new algorithms for collision detection for realtime application. They are applicable to rigid objects enclosed in boxes in order to improve the time of collision detection. The proposed algorithms, called Neuro-SAT and perceptron learning with displacement of the base frame, will be compared with the algorithm Separating Axis Test (SAT) based on the hierarchy of the OBB tree. A grasping operation of an object, with a robotic hand, was executed to test the developed algorithms. The results, of simulation experiments, reveal a great improvement in the time of collision detection.

Abstract—The foremost objective of the present research project consists developing an Intelligent Robotic System (SIR for its name in Spanish, Sistema Inteligente Robótico) that solves an unknown jigsaw puzzle in a reduced amount of time. To fulfill the objective, SIR applies pattern ...

1. INTRODUCTION It is a complex problem to find collisions in virtual envi-ronments in real-time. Collision detection is a very time consuming task. In some environments it can easily con-sume up to 50% of the total run time. In real industrial case studies, 3D virtual ...

En este trabajo se modela e implementa una estrate-gia de solución del juego "Mastermind" que emplea un algoritmo evolutivo discreto con aplicación de algunos operadores genéticos discretos, operadores de orden y operadores personalizados. Se presenta el modelo del juego, la estrategia evolutiva planteada y también los resultados obtenidos, los cuales evidencian que el modelo evolutivo consigue solucionar el juego Mastermind en una cantidad de intetntos bastante razonable. Keywords-Mastermind, algoritmos evolutivos discretos, oper-adores de orden Abstract-This paper models and implements a strategy for solving the Mastermind game using a discrete evolutionary algorithm applying some discrete genetic operators, order-based operators and custom operators. We present a model of the game, the evolutionary strategy proposed addition to the results obtained, which evidence that the evolutionary model solves the Mastermind game in a quite reasonable number of attempts. Keywords-Mastermind, discrete evolutionary algorithms, order-based operators I. INTRODUCCIÓN Mastermind c , o Master Mind es un juego de mesa para dos personas bastante conocido inventado en la década de 1970 por Mordecai Meirowitz y cuyos derechos intelectuales hoy en día son de propiedad de Pressman Toy Corporation. Este juego recuerda a un antiguo juego de lápiz y papel denominado bulls and cows con más de un siglo de existencia. La Figura 1 nos muestra la carátula de una de las primeras versiones vendidas en América del Norte en 1972. Mastermind se juega en una mesa usando un conjunto S bw de fichas blancas y negras, y un segundo conjunto S c de fichas de N colores que son un poco más grandes. El juego tiene la siguiente lógica: 1) El jugador 1 (el desafiante) escoge L fichas de colores (L = 4 en la versión original) del conjunto S c y genera una combinación que no es visible al segundo jugador. 2) El jugador 2 (el desafiado) retira algunas piezas de co-lores del conjunto S c e intenta adivinar la combinación oculta. 3) El desafiante genera un feedback con las fichas blancas y negras haciendo una fila de 0 a L fichas de acuerdo a la siguiente regla: • una ficha blanca por cada color adivinado en lugar equivocado. Fig. 1. Edición antigua de Mastermind vendidas en 1972 • una ficha negra por cada color adivinado en lugar correcto. La posición de la ficha negra no tiene relación con la verdadera posición del color adi-vinado. El juego finaliza cuando se descubre la combinación secreta, (obtención de L fichas negras) o cuando se alcanza un número máximo de intentos t max sin adivinar. Es común que t max = 15 [1]. De acuerdo a lo descrito, se observa que Mastermind es un juego relativamente simple; sin embargo, muchos investi-gadores tomaron interés en solucionarlo [2] usando técnicas de Inteligencia Artificial. Así, este juego es un problema de op-timización combinatoria que puede ser solucionado mediante un algoritmo de búsqueda. Este trabajo apunta a mostrar que, aplicando un modelo de algoritmo evolutivo discreto con operadores genéticos conven-cionales, operadores de orden y algunos operadores persona-lizados, es posible alcanzar una estrategia que encuentre una solución óptima para el juego Mastermind. A. Organización del artículo Este artículo está organizado de la siguiente manera: En la sección 2 se muestran algunos trabajos que implementan es-trategias Mastermind, en la sección 3 se tratan los Algoritmos