University of TehranJournal of Algorithms and Computation2476-277654120220601Pair mean cordial labeling of graphs1108739210.22059/jac.2022.87392ENRPonrajDepartment of Mathematics
Sri Parakalyani College
Alwarkurichi -627 412, IndiaSPrabhuResearch Scholor, Reg.No: 21121232091003, Department of Mathematics, Sri
Paramakalyani College, Alwarkurichi–627 412, Tamilnadu, IndiaJournal Article20220525In this paper, we introduce a new graph labeling called pair mean cordial labeling of graphs. Also, we investigate the pair mean cordiality of some graphs like path, cycle, complete graph, star, wheel, ladder, and comb.https://jac.ut.ac.ir/article_87392_1826c7cf2b60089d62aa5b172956101a.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601A comparison between the resolution and linear optimization of FREs defined by product t-norm and geometric mean operator11228791810.22059/jac.2022.87918ENAminGhodousianFaculty of Engineering Science, College of Engineering, University of Tehran, P.O.Box 11365-4563, Tehran, Iran.0000-0002-9224-8470SaraFalahatkarDepartment of Engineering Science, College of Engineering, University of TehranJournal Article20220630In this paper, a type of fuzzy system is firstly investigated whereby the feasible region is defined by the fuzzy relational equalities and the geometric mean as fuzzy composition. Some related basic and theoretical properties of such fuzzy relational equations are derived and the feasible region is completely determined. Also, it is proved that the feasible solutions set can be stated by one maximum solution and a finite number of minimal solutions. Moreover, a comparison is made between this region and fuzzy relational equations defined by the product t-norm. Finally, an example is described to illustrate the differences of these two FRE systems.https://jac.ut.ac.ir/article_87918_932bdf407c8c8cd879b38fb914cd068d.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Developing a New Genetic Algorithm for Selecting Efficient Project Portfolio23348794210.22059/jac.2022.87942ENMohammadMirabiDepartment of Industrial Engineering, Meybod University, Meybod, IranMohammad RezaZare BanadkoukiDepartment of Industrial Engineering, Faculty of Engineering, Meybod University, Meybod, IranJournal Article20220702selecting an efficient project portfolio among available projects is a vital decision for any project manager. The main questions are which projects can have more long-term benefits for managers or organizations. Due to the complexity of this field of research, today so many approaches are developed for project selection. Calculation time and the quality of results are two main criteria that almost all researchers have considered on them. In this research, a new hybrid genetic algorithm with new heuristic mutation and cross-over is developed to choose a good portfolio of available projects. The presented algorithm is fast and effective to reach a good result in a reasonable time. Finding a good point to start as an initial population and using a good operator a heuristic mutation and cross-over are the main points of our algorithm. To check the quality of results we compare the developed algorithms with some recent ones in the literature and comparison studies and statistical calculation demonstrate the efficiency of the new genetic algorithm to select a good portfolio.
https://jac.ut.ac.ir/article_87942_d9b3be4ba6dcbddd0b3b1640a380be99.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601$4$-total mean cordial labeling of union of some graphs with the complete bipartite graph $K_{2,n}$35468802610.22059/jac.2022.88026ENRPonrajDepartment of Mathematics
Sri Parakalyani College
Alwarkurichi -627 412, IndiaSSUBBULAKSHMISri Paramakalyani College
Alwarkurichi-627412, Tamilnadu, IndiaSSomasundaramDepartment of Mathematics
Manonmaniam sundarnar university, Abishekapatti, Tirunelveli-627012,
Tamilnadu, IndiaJournal Article20220706Let $G$ be a graph. Let $f:V\left(G\right)\rightarrow \left\{0,1,2,\ldots,k-1\right\}$ be a function where $k\in \mathbb{N}$ and $k>1$. For each edge $uv$, assign the label $f\left(uv\right)=\left\lceil \frac{f\left(u\right)+f\left(v\right)}{2}\right\rceil$. $f$ is called $k$-total mean cordial labeling of $G$ if $\left|t_{mf}\left(i\right)-t_{mf}\left(j\right) \right| \leq 1$, for all $i,j\in\left\{0,1,2,\ldots,k-1\right\}$, where $t_{mf}\left(x\right)$ denotes the total number of vertices and edges labelled with $x$, $x\in\left\{0,1,2,\ldots,k-1\right\}$. A graph with admit a $k$-total mean cordial labeling is called $k$-total mean cordial graph. In this paper, we investigate the $4$-total mean cordial labeling of some graphs derived from the complete bipartite graph $K_{2,n}$.https://jac.ut.ac.ir/article_88026_b4a0c112be1a111aca23842002f29f95.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601A Survey on Tenacity Parameter\\Part II47728802710.22059/jac.2022.88027ENDaraMoazzamiUniversity of Tehran, College of Engineering, Faculty of Engineering Science.AsiehKhoshnoodUniversity of Tehran
Department of Algorihthms and Computation, Tehran, IranJournal Article20220706In this paper, we study the edge tenacity of graphs. We will be primarily<br />interested in edge-tenacious graphs, which can be considered very stable and are somewhat analogous in edge tenacity<br />to honest graphs in edge-integrity. We show several results about edge-tenacious graphs as well as<br />find numerous classes of edge-tenacious graphs.<br />The Cartesian Products of graphs like hypercube, grids, and tori are widely used to design interconnection networks in multiprocessor computing systems.<br />These considerations motivated us to study tenacity of Cartesian products of graphs. We find the tenacity of Cartesian product of complete graphs (thus setting a conjecture stated in Cozzens and al.) and grids.<br />The Middle Graph, M(G) of a graph G is the graph obtained from G by inserting a new vertex into every edge of G and by joining by edges those pairs of these new vertices which lie on adjacent edges of G<br /> https://jac.ut.ac.ir/article_88027_7aabe4f5b8610fd31d2ec24c291c6d86.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Comparison of solutions resulted from direct problems formulated as FRE73878803810.22059/jac.2022.88038ENAminGhodousianFaculty of Engineering Science, College of Engineering, University of Tehran, P.O.Box 11365-4563, Tehran, Iran.0000-0002-9224-8470SaraZalCollege of Engineering, University of Tehran, P.O.Box 11365-4563, Tehran, Iran.Journal Article20220707In this paper, we investigate direct solution of FRE and compare their results with expected real consequences. We give an applied example formulated by a FRE problem and show that FRE defined by maximum t-conorm and an arbitrary t-norm can yield different interpretations for our example. A necessary condition and a sufficient condition are presented that guarantee FRE defined by maximum t-conorm and minimum t-norm attain the same solutions as human mind does. Also, we present a t-conorm and use it instead of maximum t-conorm in FRE to obtain solutions with highest similarity with real ones. Finally, we show that under some conditions, FRE defined by any t-conorm and any t-norm may find a solution which is not reasonable.https://jac.ut.ac.ir/article_88038_1854bbcd808bbf0954cc710f98d12240.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Approximating the Number of Lattice Points inside a Regular Polygon89988833710.22059/jac.2022.88337ENMahdiImanparastDepartment of Computer Science, University of Bojnord, Bojnord, IranJournal Article20220730We study the problem of counting the number of lattice points inside a regular polygon with $n$ sides when its center is at the origin and present an exact algorithm with $\mathcal{O}(k^{2}\log n)$ time and two approximate answers for this problem, where $k$ is the absolute value of side length of the minimum bounding box of the regular polygon. Numerical results show the efficiency of the approximations in calculating the answer to this problem.https://jac.ut.ac.ir/article_88337_67dd7eac844ccf9796bf5fca36033f08.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Relative Clustering Coefficient991088837310.22059/jac.2022.88373ENElenaTouliDepartment of Mathematics, Stockholm UniversityOscarLindbergDepartment of Mathematics, Stockholm universityJournal Article20220802In this paper, we relatively extend the definition of the global clustering coefficient to another clustering, which we call it \emph{relative clustering coefficient}. The idea of this definition is to ignore the edges in the network that the probability of having an edge is $0$. Here, we also consider a model as an example that using the relative clustering coefficient is better than the global clustering coefficient for comparing networks and also checking the properties of the networks.https://jac.ut.ac.ir/article_88373_3d678c3dff380dbd41d09aa352638319.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601An iterative method and maximal solution of Coupled algebraic Riccati equations1091238837410.22059/jac.2022.88374ENHajarAlimoradDepartment of Mathematics, Jahrom University,
P.O. Box: 74135-111, Iran.Journal Article20220802Coupled Riccati equation has widely been applied to various engineering areas such as jump linear quadratic problem, particle transport theory, and Wiener–Hopf decomposition of Markov chains. In this paper, we consider an iterative method for computing the Hermitian solution of the Coupled Algebraic Riccati Equations (CARE) which is usually encountered in control theory. We show some properties of this iterative method. Furthermore, it will also be demonstrated that the maximal solution can be obtained numerically via a certain linear or quadratic inequalities optimization problem. Numerical examples are presented and the results are compared.https://jac.ut.ac.ir/article_88374_bf25d25fdbc416b40db31da3b13f85c5.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Speeding up the Arc Consistency algorithm in Constraint Satisfaction Problems: A New Modification of AC-31251388837510.22059/jac.2022.88375ENYaserShokri Kalandaragh,Department of Advanced Technologies, University of Mohaghegh Ardabili.Journal Article20220802Dealing with constraints is always very common in real-world implementation issues. Search algorithms for real problems are also no exception. Because of the constraints in search problems (named Constraint Satisfaction Problems (CSPs)), their main solving algorithm is presented in backtracking form. The constraint propagation algorithm is an auxiliary tool to avoid facing constraint conditions as well as reducing search options. This algorithm has been presented in almost seven versions so far. In this paper, we have updated the third version of this algorithm, which is presented under the title of AC-3, from five aspects and have increased its capabilities. The most important feature of our proposed algorithm is its low time complexity. This feature has been made possible by two auxiliary criteria introduction for detecting more critical binary constraints. Faster investigation of critical constraints leads to early detection of dead-end in the search path and the search continues in this direction stops.https://jac.ut.ac.ir/article_88375_d4de1325c79b435b9a2b15e4529ed812.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601Optimizing Insurance Contract for a two-level two-period Supply Chain1391748870910.22059/jac.2022.88709ENSalehHatami Sharif AbadiIndustrial Engineering Department, Yazd University, Yazd, IRAN0000000183321624HasanHosseini NasabIndustrial Engineering Department, Yazd University, Yazd, IranMohammad BagherFakhrzadIndustrial Engineering Department, Yazd University, Yazd, IranHasanKhademi ZareiIndustrial Engineering Department, Yazd University, Yazd, IranJournal Article20220901We can apply any method for organizing a supply chain, but contracting is more viable. Among many contracts that does so, the Insurance contract is more efficient. The problem is tuning the contract's parameters (for a two-level two-period supply chain with one supplier and one retailer) to achieve the optimum point where there is more gain for everyone separately, and the predictable risks all have been covered. The insurance contract covers every predictable risk that the downstream is facing. Instead, the retailer gives the supplier some money as a side payment (Premium). So, it has two main parameters, first, the fraction ($\beta$) of every predictable loss by the retailer, which the supplier must pay, and second, the side payment (M), which the retailer must pay. We will find the best $\beta$ for a one-supplier one-retailors supply chain with two main sale periods. But for reaching the optimum state of all the insurance contract's possible forms, we designed some mathematical models based on scenarios. Then we optimize these stochastic models to find the best contract possible for 1000 initial scenarios. Every scenario indicates one possible number for price and one for demand in each period (generating 4000 possible numbers for the independent demand and price). We needed to know the maximum possible profit for the whole supply chain. First, we designed a centralized supply chain where the maximum profit is possible, then a decentralized supply chain to know the minimum of what's possible. When we have the ends of our range, we can design the final model with an insurance contract applied. In this model, we insert the $\beta$ and M into the model as the insurance contract does. First, we reduce the number of scenarios to 20 with a novel method. Then we find the optimum point by solving the final model for each $\beta$. The result was better at $\beta$=0.25. In the next step, by supposing equal negotiating power for the sides, we split the extra money into two equivalent sizes, and the M amount was measured as half of the extra money that the contract can reach. The extra money was at 0.9893 of our range means the contract earns 99.97\% of what is possible.https://jac.ut.ac.ir/article_88709_4922c1fde9a643aaa764293412392b29.pdfUniversity of TehranJournal of Algorithms and Computation2476-277654120220601On the resolution of LP-FRE defined by the convex combination operator1751868880610.22059/jac.2022.88806ENAminGhodousianFaculty of Engineering Science, College of Engineering, University of Tehran, P.O.Box 11365-4563, Tehran, Iran.0000-0002-9224-8470ParsaHadadianDepartment of Engineering Science, College of Engineering, University of TehranJournal Article20220910In this paper, a linear programming problem is investigated in which the feasible region is formed as a special type of fuzzy relational equalities (FRE). In this type of FRE, fuzzy composition is considered as the convex combination operator. It is proved that the feasible region of the problem can be written by one maximum solution and a finite number of minimal solutions. Some theoretical properties of the feasible region are derived and some necessary and sufficient conditions are also presented to determine the feasibility of the problem. Based on some structural properties of the problem, an algorithm is presented to find the optimal solutions and finally, an example is described to illustrate the algorithm.https://jac.ut.ac.ir/article_88806_4cd4d3a3fc83e7fc646b5649fb7d2cee.pdf