5 research outputs found

    A hybrid algorithm for university course timetabling problem

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    A hybrid algorithm combining the genetic algorithm with the iterated local search algorithm is developed for solving university course timetabling problem. This hybrid algorithm combines the merits of genetic algorithm and iterated local search algorithm for its convergence to global optima at the same time avoiding being get trapped into local optima. This leads to intensification of the involved search space for solutions. It is applied on a number of benchmark university course timetabling problem instances of various complexities. Keywords: timetabling, optimization, metaheuristics, genetic algorithm, iterative local searc

    Antibacterial and antioxidant activity of methanolic extract of bark of Prunus persica

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    In the present study in vitro antimicrobial and antioxidant activities of Prunus persica family rosaceae were carried out from the bark extract of the plant. The methanolic extract was tested for their antimicrobial study against gram positive and gram negative bacteria and for their antioxidant activity using scavenging activity of DPPH (1,1 diphenyl-2-picrylhydrozyl) radical method. The plant extract showed remarkable antibacterial and antioxidant activity

    Local convergence of a parameter based iteration with Holder continuous derivative in Banach spaces

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    [EN] The local convergence analysis of a parameter based iteration with Hölder continuous first derivative is studied for finding solutions of nonlinear equations in Banach spaces. It generalizes the local convergence analysis under Lipschitz continuous first derivative. The main contribution is to show the applicability to those problems for which Lipschitz condition fails without using higher order derivatives. An existence-uniqueness theorem along with the derivation of error bounds for the solution is established. Different numerical examples including nonlinear Hammerstein equation are solved. The radii of balls of convergence for them are obtained. Substantial improvements of these radii are found in comparison to some other existing methods under similar conditions for all examples considered.The authors thank the referees for their valuable comments which have improved the presentation of the paper. The authors thankfully acknowledge the financial assistance provided by Council of Scientific and Industrial Research (CSIR), New Delhi, India.Singh, S.; Gupta, DK.; Badoni, RP.; Martínez Molada, E.; Hueso Pagoaga, JL. (2017). Local convergence of a parameter based iteration with Holder continuous derivative in Banach spaces. CALCOLO. 54(2):527-539. doi:10.1007/s10092-016-0197-9S527539542Argyros, I.K., Hilout, S.: Numerical methods in nonlinear analysis. World Scientific Publ. Comp, New Jersey (2013)Argyros, I.K., Hilout, S., Tabatabai, M.A.: Mathematical modelling with applications in biosciences and engineering. Nova Publishers, New York (2011)Singh, S., Gupta, D.K., Martínez, E., Hueso, J.L.: Semilocal and local convergence of a fifth order iteration with Fréchet derivative satisfying Hölder condition. Appl. Math. Comput. 276, 266–277 (2016)Traub, J.F.: Iterative methods for the solution of equations. Prentice-Hall, Englewood Cliffs (1964)Rall, L.B.: Computational solution of nonlinear operator equations, reprint edn. R. E. Krieger, New York (2007)Cordero, A., Ezquerro, J.A., Hernández-Verón, M.A., Torregrosa, J.R.: On the local convergence of a fifth-order iterative method in Banach spaces. Appl. Math. Comput. 251, 396–403 (2015)Argyros, I.K., Hilout, A.S.: On the local convergence of fast two-step Newton-like methods for solving nonlinear equations. J. Comput. Appl. Math. 245, 1–9 (2013)Argyros, I.K., Behl, R., Motsa, S.S.: Local convergence of an efficient high convergence order method using hypothesis only on the first derivative. Algorithms 8, 1076–1087 (2015)Kantorovich, L.V., Akilov, G.P.: Functional analysis. Pergamon Press, Oxford (1982)Argyros, I.K., Magreñán, A.A.: A study on the local convergence and dynamics of Chebyshev-Halley-type methods free from second derivative. Numer. Algorithms 71, 1–23 (2016)Li, D., Liu, P., Kou, J.: An improvement ofthe Chebyshev-Halley methods free from second derivative. Appl. Math. Comput. 235, 221–225 (2014)Argyros, I.K., George, S.: Local convergence of deformed Halley method in Banach space under Holder continuity conditions. J. Nonlinear Sci. Appl. 8, 246–254 (2015)Argyros, I.K., Khattri, S.K.: Local convergence for a family of third order methods in Banach spaces. J. Math. 46, 53–62 (2014)Argyros, I.K., George, S., Magreñán, A.A.: Local convergence for multi-point-parametric Chebyshev-Halley-type methods of higher convergence order. J. Comput. Appl. Math. 282, 215–224 (2015)Argyros, I.K., George, S.: Local convergence of modified Halley-like methods with less computation of inversion. Novi. Sad. J. Math. 45, 47–58 (2015)Xiao, X.Y., Yin, H.W.: Increasing the order of convergence for iterative methods to solve nonlinear systems. Calcolo (2015). doi: 10.1007/s10092-015-0149-9Martínez, E., Singh, S., Hueso, J.L., Gupta, D.K.: Enlarging the convergence domain in local convergence studies for iterative methods in Banach spaces. Appl. Math. Comput. 281, 252–265 (2016

    An Exploration and Exploitation-Based Metaheuristic Approach for University Course Timetabling Problems

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    The university course timetable problem (UCTP) is known to be NP-hard, with solution complexity growing exponentially with the problem size. This paper introduces an algorithm that effectively tackles UCTPs by employing a combination of exploration and exploitation strategies. The algorithm comprises two main components. Firstly, it utilizes a genetic algorithm (GA) to explore the search space and discover a solution within the global optimum region. Secondly, it enhances the solution by exploiting the region using an iterated local search (ILS) algorithm. The algorithm is tested on two common variants of UCTP: the post-enrollment-based course timetable problem (PE-CTP) and the curriculum-based course timetable problem (CB-CTP). The computational results demonstrate that the proposed algorithm yields competitive outcomes when compared empirically against other existing algorithms. Furthermore, a t-test comparison with state-of-the-art algorithms is conducted. The experimental findings also highlight that the hybrid approach effectively overcomes the limitation of local optima, which is encountered when solely employing GA in conjunction with local search
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