University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Sweep Line Algorithm for Convex Hull Revisited 1 14 71276 10.22059/jac.2019.71276 EN Keivan Borna Faculty of Mathematics and Computer Science, Kharazmi University, Tehran, Iran Journal Article 2018 07 14 Convex hull of some given points is the intersection of all convex sets containing them. It is used as primary structure in many other problems in computational geometry and other areas like image processing, model identification, geographical data systems, and triangular computation of a set of points and so on. Computing the convex hull of a set of point is one of the most fundamental and important problems of computational geometry. In this paper a new algorithm is presented for computing the convex hull of a set of random points in the plane by using a sweep-line strategy. The sweep-line is a horizontal line that is moved from top to bottom on a map of points. Our algorithm is optimal and has time complexity $O(nlogn)$ where $n$ is the size of input. https://jac.ut.ac.ir/article_71276_3582cee25a2b43cca2ab21531a548870.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Intelligent application for Heart disease detection using Hybrid Optimization algorithm 15 27 71277 10.22059/jac.2019.71277 EN Marzieh Eskandari Department of computer science, Alzahra University, Tehran, Iran Zeinab Hassani Department of computer science, Kosar University of Bojnord, Iran. Journal Article 2018 03 12 Prediction of heart disease is very important because it is one of the causes of death around the world. Moreover, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side effects it. Machine learning algorithms are able to identify an effective pattern for diagnosis and treatment of the disease and identify effective factors in the disease. this paper is investigated a new hybrid algorithm of Whale Optimization and Dragonfly algorithm using a machine learning algorithm. the hybrid algorithm employs a Support Vector Machine algorithm for effective Prediction of heart disease. Proposed method is evaluated by Cleveland standard heart disease dataset. The experimental result indicates that the SVM accuracy of 88.89 $\%$ and nine features are selected in this respect. https://jac.ut.ac.ir/article_71277_7cd80aac11e7944161c87936cb9b6ffe.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Algorithm for finding the largest inscribed rectangle in polygon 29 41 71280 10.22059/jac.2019.71280 EN Zahraa Marzeh Department of computer science, Shahid Beheshti University, G.C., Tehran, Iran. Maryam Tahmasbi Department of computer science, Shahid Beheshti University, G.C., Tehran, Iran. Narges Mirehi Department of computer science, Shahid Beheshti University, G.C., Tehran, Iran. Journal Article 2018 08 11 In many industrial and non-industrial applications, it is necessary to identify the largest inscribed rectangle in a certain shape. The problem is studied for convex and non-convex polygons. Another criterion is the direction of the rectangle: axis aligned or general. In this paper a heuristic algorithm is presented for finding the largest axis aligned inscribed rectangle in a general polygon. Comparing with stare of the art, the rectangles resulted from our algorithm have bigger area. We also proposed an approach to use the algorithm for finding a rectangle with general direction. https://jac.ut.ac.ir/article_71280_2a21de484e568a9e396458a5930ca06a.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Optimization of profit and customer satisfaction in combinatorial production and purchase model by genetic algorithm 43 54 71290 10.22059/jac.2019.71290 EN Fatemeh Ganji Department of Industrial Engineering, Gopayegan University of Technology. Golpayegan, Iran Zahrasadat Zamani Department of Industrial Engineering, Gopayegan University of Technology, Golpayegan, Iran. Journal Article 2018 06 10 Optimization of inventory costs is the most important goal in industries. But in many models, the constraints are considered simple and relaxed. Some actual constraints are to consider the combinatorial production and purchase models in multi-products environment. The purpose of this article is to improve the efficiency of inventory management and find the economic order quantity and economic production quantity that can minimize the cost of inventory and customer satisfaction. In this study, the models with these targets in combinatorial production and purchase systems with the assumption the warehouse and budget constraints are proposed. Since a long time for solving the problem with an exact method is required, we develop a genetic algorithm. To evaluate the efficiency of the proposed algorithm, test problems with different sizes of the problem in the range from 1 to 2000 jobs, are generated. The results show that the genetic method is efficient to determine economic order quantity and economic production quantities. The computational results demonstrate that the average error of the solution is 10.93\%.  https://jac.ut.ac.ir/article_71290_54acb939a91d944d7b9986a358240f47.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Max-Min averaging operator: fuzzy inequality systems and resolution 55 70 71296 10.22059/jac.2019.71296 EN A. Ghodousian University of Tehran, College of Engineering, Faculty of Engineering Science Tarane Azarnejad Department of Algorithms and Computation, Unversity of Tehran. Farnood Samie Yousefi Department of Algorithms and Computation, Unversity of Tehran. Journal Article 2018 07 10  Minimum and maximum operators are two well-known t-norm and s-norm used frequently in fuzzy systems. In this paper, two different types of fuzzy inequalities are simultaneously studied where the convex combination of minimum and maximum operators is applied as the fuzzy relational composition. Some basic properties and theoretical aspects of the problem are derived and four necessary and sufficient conditions are presented. Moreover, an algorithm is proposed to solve the problem and an example is described to illustrate the algorithm. https://jac.ut.ac.ir/article_71296_f7a3e4157a635572142f26c72577ac0f.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 A Closed-Form Solution for Two-Dimensional Diffusion Equation Using Crank-Nicolson Finite Difference Method 71 77 71297 10.22059/jac.2019.71297 EN Iman Shojaei Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506, USA. Hossein Rahami School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran 0000-0001-7540-8412 Journal Article 2018 08 15 In this paper a finite difference method for solving 2-dimensional diffusion equation is presented. The method employs Crank-Nicolson scheme to improve finite difference formulation and its convergence and stability. The obtained solution will be a recursive formula in each step of which a system of linear equations should be solved. Given the specific form of obtained matrices, rather than solving the problem in each step using conventional iterative methods, a closed-form solution is formulated.. https://jac.ut.ac.ir/article_71297_5397798f2c99c329aa87ce4d7a549428.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Correlation Coefficients for Hesitant Fuzzy Linguistic Term Sets 79 89 71533 10.22059/jac.2019.71533 EN Gholamreza Hesamian Department of Statistics, Payame Noor University, Tehran 19395-3697, Iran Mohammad Ghasem Akbari Department of Mathematical Sciences, University of Birjand, Birjand, 615-97175, Iran Journal Article 2018 06 11 Here are many situations in real applications of decision making where we deal with uncertain conditions.  Due to the different sources of uncertainty,  since its original definition of fuzzy sets in 1965 \cite{zadeh1965},  different generalizations and extensions of fuzzy sets have been introduced: Type-2 fuzzy sets \cite{6,13}, Intuitionistic fuzzy sets \cite{1}, fuzzy multi-sets \cite{37} and etc. However, in such cases, it is suitable for experts to provide their preferences or assessments by using linguistic information rather than quantitative values. https://jac.ut.ac.ir/article_71533_8b47cba0e625d834f3062d9fc0846f0a.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Some new restart vectors for explicitly restarted Arnoldi method 91 105 71545 10.22059/jac.2019.71545 EN Zeinab Abadi Department of mathematical Sciences, Faculty of science, Yazd University Seyed Abolfazl Shahzadeh Fazeli Department of Computer Science, Yazd University, Yazd, Iran. 0000-0002-3724-8689 Seyed Mehdi Karbassi Department of Mathematical Science, Yazd University, Yazd, Iran. Journal Article 2019 01 03 The explicitly restarted Arnoldi method (ERAM) can be used to find some eigenvalues of large and sparse matrices. However, it has been shown that even this method may fail to converge. In this paper, we present two new methods to accelerate the convergence of ERAM algorithm. In these methods, we apply two strategies for the updated initial vector in each restart cycles. The implementation of the methods have been tested by numerical examples. The results show that we can obtain a good acceleration of the convergence compared to original ERAM. https://jac.ut.ac.ir/article_71545_bcf299911ac37b00226dbfee3c81e840.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 $k$-Total difference cordial graphs 121 128 71773 10.22059/jac.2019.71773 EN R Ponraj Department of Mathematics Sri Parakalyani College Alwarkurichi -627 412, India S.Yesu Doss Philip Research Scholar,Department of Mathematics, Manonmaniam sundarnar university, Abishekapatti, Tirunelveli-627 012, Tamilnadu, India. R Kala Manonmaniam Sundaranar University, Tirunelveli-627012, Tamilnadu, India. Journal Article 2018 05 14 Let $G$ be a graph. Let $f:V(G)\to\{0,1,2, \ldots, k-1\}$ be a map where $k \in \mathbb{N}$ and $k>1$. For each edge $uv$, assign the label $\left|f(u)-f(v)\right|$. $f$ is called a $k$-total difference cordial labeling of $G$ if $\left|t_{df}(i)-t_{df}(j)\right|\leq 1$, $i,j \in \{0,1,2, \ldots, k-1\}$ where $t_{df}(x)$ denotes the total number of vertices and the edges labeled with $x$.A graph with admits a $k$-total difference cordial labeling is called a $k$-total difference cordial graphs. We investigate $k$-total difference cordial labeling of some graphs and study the $3$-total difference cordial labeling behaviour of star,bistar,complete bipartiate graph,comb,wheel,helm,armed crown etc. https://jac.ut.ac.ir/article_71773_84efb68209e5c4b9e46a7a8357792b40.pdf
University of Tehran Journal of Algorithms and Computation 2476-2776 51 1 2019 06 01 Detour Monophonic Graphoidal Covering Number of Corona Product Graph of Some Standard Graphs with the Wheel 129 145 71870 10.22059/jac.2019.71870 EN P. Titus Assistant Professor Department of Mathematics University College of Engineering Nagercoil Anna University, Tirunelveli Region Tamil Nadu, India. S. Santha Kumari Anna University, Tirunelveli Region Nagercoil - 629 004, India. Journal Article 2018 09 05 A chord of a path $P$ is an edge joining two non-adjacent vertices of $P$. A path  $P$ is called a monophonic path if it is a chordless path. A longest $x-y$ monophonic path is called an $x-y$ detour monophonic path. A  detour monophonic graphoidal cover of a graph $G$ is a collection $\psi_{dm}$ of detour monophonic paths in $G$ such that every vertex of $G$ is an internal vertex  of at most one  detour monophonic path in $\psi_{dm}$ and every edge of $G$ is in exactly one  detour monophonic path in $\psi_{dm}$. The minimum cardinality of a  detour monophonic graphoidal cover of $G$ is called the  detour monophonic graphoidal covering number of $G$ and is denoted by $\eta_{dm}(G)$. In this paper, we find the  detour monophonic graphoidal covering number of corona product of wheel with some standard graphs https://jac.ut.ac.ir/article_71870_c0c04234c24fab5bc234fb05354c2361.pdf