A selection hyper-heuristic is a search method that controls a prefixed set of low-level heuristics for solving a given computationally difficult problem. This study investigates a learning-via demonstrations approach generating a selection hyper-heuristic for Open Vehicle Routing Problem (OVRP). As a chosen 'expert' hyper-heuristic is run on a small set of training problem instances, data is collected to learn from the expert regarding how to decide which low-level heuristic to select and apply to the solution in hand during the search process. In this study, a Time Delay Neural Network (TDNN) is used to extract hidden patterns within the collected data in the form of a classifier , i.e an 'apprentice' hyper-heuristic, which is then used to solve the 'unseen' problem instances. Firstly, the parameters of TDNN are tuned using Taguchi orthogonal array as a design of experiments method. Then the influence of extending and enriching the information collected from the expert and fed into TDNN is explored on the behaviour of the generated apprentice hyper-heuristic. The empirical results show that the use of distance between solutions as an additional information collected from the expert generates an apprentice which outperforms the expert algorithm on a benchmark of OVRP instances.
<span id="docs-internal-guid-a29e641b-7fff-1dc7-f2b4-6f5488c7c0a5"><span>The stock market is one of the investment choices that always have traction from time to time. Aside from being a means of corporate funding, investing in the stock market can benefit investors. Investing also has a higher risk because the pattern of stock prices is volatile, which is caused by internal and external factors. One external factor that affects stock prices is the macro-economic, where these factors are events that occur in a country where one of the economic sectors affected is stock prices. Investors often feel confused about the right time in decisions making related to buying or selling stock. One way to look at how the prospect of stock prices is a stock price forecasting activity. For this study, we will be making use of the recurrent neural network (RNN) to forecast stock prices for the next periods. This research involves two variables: the closing stock price and the rupiah exchange rate against the dollar for the daily period. We achieve a MAPE value of 1.546% for RNN model without the variable foreign exchange rate and 1.558% for the RNN model that uses the foreign exchange rate against the dollar.</span></span>
Scheduling exams in colleges are a complicated job that is difficult to solve conventionally. Exam timetabling is one of the combinatorial optimization problems where there is no exact algorithm that can answer the problem with the optimum solution and minimum time possible. This study investigated the University of Toronto benchmark dataset, which provides 13 real instances regarding the scheduling of course exams from various institutions. The hard constraints for not violate the number of time slots must be fulfilled while paying attention to fitness and running time. Algorithm of largest degree, hill climbing, and tabu search within a hyper-heuristic framework is investigated with regards to each performance. This study shows that the Tabu search algorithm produces much lower penalty value for all datasets by reducing 18-58% from the initial solution.
Diabetes melitus merupakan penyakit metabolik dimana penderita diabetes tidak bisa memproduksi insulin dalam jumlah cukup atau tubuh tidak mampu menggunakan insulin secara efektif sehingga terjadi kelebihan gula di dalam darah. Kondisi ini baru dirasakan setelah terjadi komplikasi lanjut pada organ tubuh. Pada penderita diabetes melitus, dapat terjadi komplikasi pada tingkat sel dan anatomik. Komplikasi kronik yang disebabkan oleh diabetes melitus dapat terjadi pada pembuluh darah besar (makrovaskuler) dan pembuluh darah kecil (mikrovaskuler). Komplikasi makrovaskuler yang umum terjadi adalah pembekuan darah pada otak, penyakit jantung koroner, dan stroke. Sedangkan komplikasi mikrovaskuler yang umum terjadi adalah hiperglikemia dan retinopati (kebutaan) [1]. Retinopati diabetik merupakan kerusakan retina yang diakibatkan oleh komplikasi dari diabetes melitus [2]. Menurut data dari WHO pada tahun 2015, Indonesia menempati posisi ke tujuh di dunia untuk prevalensi penderita diabetes tertinggi di dunia dengan estimasi penderita diabetes sebesar 10 juta orang dari jumlah penderita diabetes di dunia sebesar 415 juta jiwa. Berdasarkan penelitian yang dilakukan oleh INFORMASI ARTIKEL
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