Multipopulation Genetic Algorithm Based on GPU for Solving TSP Problem

A GPU-based Multigroup Genetic Algorithm was proposed, which parallelized the traditional genetic algorithm with a coarse-grained architecture island model. The original population is divided into several subpopulations to simulate different living environments, thus increasing species richness. For each subpopulation, different mutation rates were adopted, and the crossover results were optimized by combining the crossover method based on distance. The adaptive mutation strategy based on the number of generations was adopted to prevent the algorithm from falling into the local optimal solution. An elite strategy was adopted for outstanding individuals to retain their superior genes. The algorithm was implemented with CUDA/C, combined with the powerful parallel computing capabilities of GPUs, which greatly improved the computing efficiency. It provided a new solution to the TSP problem.

Improving Scalability and Balancing the Network Load Using Adaptive Multiparent Crossover Method in Wireless Sensor Networks

Wireless sensor network comprises of scattered sensors to sense, monitor and aggregate the sensed information. The major issue in a wireless sensor network is to balance network load and to maintain less energy consumption where multi parent crossover method is considered. Multiparent cross over method will generate offspring from parent and aims at managing the load. In this paper a comparative study of different algorithms is done where the load balancing and energy consumption issue has been resolved.

Use of two-point models in “Model choice in time-series studies of air pollution and mortality”

In this work, a new technique is proposed to study short-term exposure and adverse health effects. The presented approach uses hierarchical clusters with the following structure: each pair of two sequential days in 1 year is embedded in the year. We have 183 clusters per year with the embedded structure <year:2 days>. Time-series analysis is conducted using a conditional Poisson regression with the constructed clusters as a stratum. Unmeasured confounders such as seasonal and long-term trends are not modelled but are controlled by the structure of the clusters. The proposed technique is illustrated using four freely accessible databases, which contain complex simulated data. These data are available as the compressed R workspace files. Results based on the simulated data were very close to the truth based on the presented methodology. In addition, the case-crossover method with 1-month and 2-week window, and a conditional Poisson regression on 3-day clusters as a stratum, was also applied to the simulated data. Difficulties (high type I error rate) were observed for the case-crossover method in the presence of high concurvity in the simulated data. The proposed methods using various forms of a stratum were further applied to the Chicago mortality data. The considered methods have often different qualitative and quantitative estimations.

Penerapan Algoritma Genetika Pada Penentuan Lintasan Terpendek Jalur Bus Rapid Transit Makassar

Bus Rapid Transit is a bus system that is fast, convenient, safe and on time from infrastructure, vehicles, and schedules. As a graph problem, BRT representation in a graph is done by assuming the bus stop as a vertex and the distance between bus stops is an edge. The problem examined in this paper is to find out the path that passes through all the bus stops with the smallest total distance, where the trip starts and ends at the same point, and all bus stops are crossed exactly once. The method used is the Genetic Algorithm, which works using objective and fitness functions, and combines selection, crossover and mutation operators to find the best solution. Using the roulette wheel, OX crossover method and a 0.07 of the probability of mutation, the distance of traverse from and to the departure point after passing all bus stops is 19.66 km or 12.22 miles.

An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator

The traveling salesman problem (TSP) is a famous NP-hard problem in the area of combinatorial optimization. It is utilized to locate the shortest possible route that visits every city precisely once and comes back to the beginning point from a given set of cities and distance. This paper proposes an efficient and effective solution for solving such a query. A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. The crossover operator (MWVOSX) chooses a particular order from multiple orders which have the minimum cost and takes the remaining from the other parent in backward and forward order. Then it creates two new offspring. Further, it selects the least weight new offspring from those two offspring. The efficiency of the proposed algorithm is compared to the classical genetic algorithm. Comparisons show that our proposed algorithm provides much efficient results than the existing classical genetic algorithm.

IMPLEMENTATION OF MULTICRITERIA MOVING AVERAGE CROSSOVER INDICATORS AS THE BASIS FOR TECHNICAL ANALYSIS DECISION MAKING AT THE FUTURES EXCHANGE

The purpose of this paper is to minimize the risk of trading option and futures through conducting technical analysis utilizing Double Crossover Method. Hence, it tries to seek the answer on some problems including trading foreign exchange without having to make official and uncomplicated investments, trading without having to spend a lot of time, testing double crossover methods in a short time, and how to determine the most effective double crossover methods with multi-criteria considerations. This research utilized both Backtesting and Analytical Hierarchy Process (AHP) methods. Based on the results of these stages, it was found that MT4 FXDD, SMA 5 - 10 pairs on H4 Timeframes, Expert Advisors, and Back testing were the answers to the existing problems. For general investors, this strategies support their activities on getting real and efficient foreign exchange trading facilities without joining procedural and official investments in the futures exchange.Efficient decision makers tools can be utilized in trading to avoid or minimize the loss by6applying the most effective double crossover method priority used as a technical analysis in trading foreign exchange based on test results. Trading foreign exchange previously was utilizing single lines moving average that has some waeknesses. This study tries to shed the light of double crossover method, utilizing two lines of moving averages to generate trading signals effectively and accurately in minimizing loss. Keywords—F31 Foreign Exchange, G13 Futures Pricing, F17 Trade Forecasting and Simulation, E22 Investment Abstrak Artikel ini bertujuan untuk meminimalkan risiko trading option and futures melalui penggunaan analisis teknis dengan menggunakan Metode Double Crossover. Oleh karena itu, penelitian ini mencoba mencari jawaban pada beberapa masalah terkait dengan hal berikut yaitu: bagaimana melakukan perdagangan valuta asing tanpa harus melakukan investasi resmi dan tidak rumit, bagaimana melakukan perdagangan tanpa harus menghabiskan banyak waktu, bagaimana menguji metode Double Crossover dalam waktu singkat, dan bagaimana menentukan metode Double Cross over yang paling efektif dengan pertimbangan multi-kriteria. Penelitian ini menggunakan metode Backtesting dan Analytical Hierarchy Process (AHP). Berdasarkan hasil penelitian ditemukan bahwa jawaban dari masalah yang dicari dalam penelitian ini secara berurutan yaitu menggunakan aplikasi MT4 FXDD, SMA 5 - 10 pasang pada H4 Timeframes, Expert Advisors, dan Backtesting. Hasil penelitian ini dapat dimanfaatkan oleh investor umum karena strategi ini mendukung kegiatan mereka dalam mendapatkan fasilitas perdagangan valuta asing yang nyata dan efisien tanpa bergabung dengan investasi resmi dan penuh prosedural di bursa berjangka. Selanjutnya, Alat pembuat keputusan yang efisien dapat dimanfaatkan oleh investor untuk menghindari atau meminimalkan kerugian dengan menerapkan prioritas metode double crossover paling efektif yang digunakan sebagai analisis teknis dalam perdagangan valuta asing berdasarkan hasil tes. Pengambilan keputusan dalam perdagangan valuta asing sebelumnya hanya mengacu pada penggunakan garis tunggal Moving average yang memiliki kelemahan. Studi ini mencoba untuk menjelaskan metode double crossover, yaitu metode yang memanfaatkan dua garis moving average untuk menghasilkan sinyal perdagangan secara efektif dan akurat dalam pengambilan keputusan dan meminimalkan kerugian. Kata Kunci— Valuta Asing (F31), Harga Saham (G13), Perkiraan dan Simulasi Perdagangan (F17), Investasi (E22)

IMPLEMENTATION OF MULTI-CRITERIA MOVING AVERAGE CROSSOVER INDICATORS AS THE BASIS FOR TECHNICAL ANALYSIS DECISION MAKING AT THE FUTURES EXCHANGE

The purpose of this paper is to minimize the risk of trading option and futures through conducting technical analysis utilizing Double Crossover Method. Hence, it tries to seek the answer on some problems such as: foreign exchange tradingwithout having to make official and uncomplicated investments, trading without having to spend a lot of time, testing double crossover methods in a short time, and how to determine the most effective double crossover methods with multi-criteria considerations. Four methods were used which included the review, pre-testing, testing, and drawing conclusions. Based on the results of these stages, it was found that MT4 FXDD, SMA 5 - 10 pairs on H4 Timeframes, Expert Advisors, and Backtesting were the answers to the existing problems. Based on the aforementioned results, there are some suggestion for general investors, this strategies support their activities on getting real and efficient foreign exchange trading facilities without Joining procedural and official investments in the futures exchange; utilizing efficient decision makers tools in trading to avoid or minimize the loss, applying the most effective Double Crossover Method priority used as a technical analysis in trading foreign exchange based on test results. At last, this study explains the application of the double crossover method, which is a method that utilizes two moving average lines to generate a more effective and accurate trading signal for making decision and minimizes losses compared to the use of a single moving average. Keywords—F31 Foreign Exchange; G13 Futures Pricing; F17 Trade Forecasting and Simulation; E22 Investment. Abstrak Tujuan dari artikel ini yaitu untuk meminimalkan risiko trading option and futures melalui penggunaan analisis teknis dengan menggunakan Metode Double Crossover. Oleh karena itu, penelitian ini mencoba mencari jawaban pada beberapa masalah terkait dengan hal berikut yaitu: bagaimana melakukan perdagangan valuta asing tanpa harus melakukan investasi resmi dan tidak rumit, bagaimana melakukan perdagangan tanpa harus menghabiskan banyak waktu, bagaimana menguji metode Double Crossover dalam waktu singkat, dan bagaimana menentukan metode Double Crossoveryang paling efektif dengan pertimbangan multi-kriteria. Empat metode digunakan yang meliputi tinjauan, pra-pengujian, pengujian, dan menarik kesimpulan. Berdasarkan hasil dari tahap-tahap ini, ditemukan bahwa jawaban dari masalah yang dicari dalam penelitian ini secara berurutan yaitu menggunakanaplikasi MT4 FXDD, SMA 5 - 10 pasang pada H4 Timeframes, Expert Advisors, dan Backtesting adalah. Berdasrakan hasil diatas, ada beberapa saran bagi investor atau masyarakat umum, strategi ini mendukung kegiatan mereka dalam mendapatkan fasilitas perdagangan valuta asing yang nyata dan efisien tanpa bergabung dengan investasi resmi dan penuh prosedural di bursa berjangka; Memanfaatkan alat pembuat keputusan yang efisien dalam perdagangan untuk menghindari atau meminimalkan kerugian, menerapkan prioritas Metode Double Crossover paling efektif yang digunakan sebagai analisis teknis dalam perdagangan valuta asing berdasarkan hasil tes. Nilai terpenting dari penelitian ini menjelaskan penggunaan metode double crossover, yaitu metode yang memanfaatkan dua garis moving average untuk menghasilkan sinyal perdagangan yang lebih efektif dan akurat dalam pengambilan keputusan dan meminimalkan kerugian dibandingkan dengan penggunaan single moving average. Kata Kunci— Valuta Asing (F31); Harga Saham (G13); Perkiraan dan Simulasi Perdagangan (F17); Investasi (E22).

PENJADWALAN MATA KULIAH MENGGUNAKAN ALGORITMA GENETIKA DI STT WASTUKANCANA PURWAKARTA

Generating a study at STT Wastukancana Purwakarta is strongly important to get an effective way to study. As the allocation of rooms to the schedule made is still manual, it is possible there are some room service clashes. To solve that problem, a study scheduling using computerization is needed in order to make no clash of room service. The use of genetic algorithm to solve the problem is able to get the optimal solution in generating the schedule with chromosome representative as an integer from each of data primary key, the beginning of population initialization, the selection with rank-selection method, two-points crossover method, and mutation. From the test, the result points out that the optimal schedule with 416 pengampu data is generated when a number of population are 30, a number of generations are 150, the crossover probability value (Pc) is 0.4, and the mutation probability value (Pm) is 0.37.

Analysis Determination of Genetic Algorithm Crossover Point Problem in Travelling Salesman Problem

Travelling Salesman Problem (TSP) is an optimization problem that can be applied to a variety of activities. Highlights of theTSPproblem is how the salesman can manage the journey so that the distance by which this is the optimum route is the best minimum distance. This study was formulated with the effect of determining the crossover point, especially probabilities of crossover in the search for the optimal route to theTSP. One goal of this research is to find the value of a good crossover probability in achieving optimal route. Crossover method used in this study is a partially mapped crossover (PMX). Selection is used Roulette wheel selection. From the tests carried out by using 20%, 40%, 60%, 80% and 99% can be found that a good crossover probability is 99%, with the determination of mutations worth of 0.05%. The number of generation is the generation 10000. Optimal route obtained from the data bays29.tsp is 10463.

Temporal-spatial distribution of oceanic vertical deflections determined by TOPEX/Poseidon and Jason-1/2 missions

Deflections of the Vertical (DOV) are essential data in the geodetic observation reduce, the earth gravity field and geoid model refinement, and the mass earth change. The meridional and prime vertical components of global oceanic DOVs are estimated from altimetry data of TOPEX/Poseidon, Jason-1, and Jason-2, through 1992 to 2013 with the crossover method, to analyze the temporal-spatial distribution of marine DOVs. Comparing with the EGM2008-modelled DOVs, precisions of meridional and prime vertical components can be up to 0.98” and 1.02”, respectively. The time series of annual mean DOVs from 1992 to 2013 are studied to get the annual variation law. Annual changes of meridional and prime vertical components are small over most oceans. But the annual changes are significant over oceans with large submarine topography undulations. The spatial distribution of oceanic DOVs is also analyzed. The absolute DOVs over oceans around lands, islands, and large oceanic trenches are greater than those over the other oceans. The meridional and prime vertical components are consistent with the longitude and latitude directions, respectively. ResumenLas Desviaciones de la Vertical (DOV, del inglés Deflections of the Vertical) son información esencial en la simplificación de la observación geodésica, el campo gravitatorio terrestre y el perfeccionamiento del modelo geoide, y el cambio de la masa terrestre. Se estimaron los componentes meridional y principal vertical de las desviaciones de la vertical oceánica global con la información altimétrica de TOPEX/Poseidón, Jason 1 y Jason 2, de 1992 a 2013, con un método de cruce para analizar la distribución espacio-temporal de las desviaciones de la vertical marinas. Comparadas con las desviaciones de la vertical obtenidas con el modelo EGM2008 (Modelo de Gravitación de la Tierra), la precisión de los componentes meridional y principal vertical puede aumentarse 0.98" y 1.02", respectivamente. Se estudiaron las series temporales de la media anual de las desviaciones de la vertical desde 1992 a 2013 para obtener la ley anual de variación. Los cambios anuales de los componentes meridional y principal vertical son muy pequeñas en la mayoría de los océanos. Sin embargo, los cambios anuales son mayores en aquellos océanos con una topografía submarina de grandes ondulaciones. También se analizó la distribución espacial de las desviaciones de la vertical oceánicas. Las desviaciones de la vertical absolutas alrededor de los continentes, islas y fosas oceánicas mayores son superiores que aquellas sobre los otros océanos. Los componentes meridional y vertical principal son consistentes con las direcciones de la longitud y la latitud, respectivamente.