Search

Let Xn = {1, 2, 3, ⋯, n}. Let Pn and Tn denote the partial and full transformation semigroups on Xn. For n = 1, 2, 3, 4, we obtain the polarity in a signed order-preserving, order-decreasing and reversing partial transformation semigroups by the order (n + 1)n of Pn. [ABSTRACT FROM AUTHOR]

In this note, we obtain a new class of Hardy's integral inequalities by using a fairly elementary analysis. This result simplifies the proofs of some existing results and two possible constants are shown in the limit Hardy-type version. [ABSTRACT FROM AUTHOR]

Some dynamic inequalities of Opial-type inequalities are generalized through Jensen's and Hölder's inequalities for convex functions. In particular, Hua's and Rozanova's inequalities on time scales are refined. [ABSTRACT FROM AUTHOR]

The purpose of this article is to prove the convergence and stability of Mann and Ishikawa iterative procedures by applying λ-generalized, Geraghty and Ciric contractive conditions in a complete G-metric space. [ABSTRACT FROM AUTHOR]

In this paper, we establish and prove some common fixed points for self-maps in a complete cone metric space that generalize and improve earlier results in the literature. [ABSTRACT FROM AUTHOR]

In this work, air crew scheduling problem is formulated using a practical case of IRS Airline, Nigeria. The formulated Integer Program was solved using TORA Optimization software and a recommended solution was obtained with the optimal value of 3183 minutes and 13 xvariables as pairings. [ABSTRACT FROM AUTHOR]

It has been proved that the conventional conjugate gradient Method Algorithm (CGM) converges in at most n iterations in a well posed quadratic functional problems. This work used Fibonacci Scheme on Gradient Method (GM) to solve quadratic functional problems and the results are favorable and comparable with CGM algorithm. [ABSTRACT FROM AUTHOR]

We considered Computational results with Fibonacci scheme for Gradient method. In Particular, Fibonacci scheme is used as against the arbitrary perturbation term, lambda (λ) in Gradient method. It is proved that Fibonacci technique converges to the solution if the interval of uncertainty is known and N is large for the Fibonacci sequence in Gradient Method. [ABSTRACT FROM AUTHOR]

Some Computational algorithms are considered in this work. Specifically Conjugate Gradient (CGM), Fletcher-Reeves, Steepest Descent and Fibonacci methods are considered for minimizing some quadratic functional. The convergence rate of CGM and Fletcher-Reeves converges at the same time. It is also proved that Fibonacci technique will converge to its solution if the interval of uncertainty is known and N is large for the Fibonacci sequence. [ABSTRACT FROM AUTHOR]