Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

      This paper presents an alternative method for developing effective embedded optimized Runge-Kutta (RK) algorithms to solve oscillatory problems numerically.   The embedded scheme approach has algebraic orders of 5 and 4. By transforming second-order ordinary differential equations (ODEs) into their first-order counterpart, the suggested approach solves first-order ODEs. The amplification error, phase-lag, and first derivative of the phase-lag are all nil in the embedded pair. The alternative method’s absolute stability is demonstrated. The numerical tests are conducted to demonstrate the effectiveness of the developed approach in comparison to other RK approaches. The alternative approach outperforms the current RK methods

An improved Metal Solar Wall (MSW) with integrated thermal energy storage is presented in this research. The proposed MSW makes use of two, combined, enhanced heat transfer methods. One of the methods is characterized by filling the tested ducts with a commercially available copper Wired Inserts (WI), while the other one uses dimpled or sinusoidal shaped duct walls instead of plane walls. Ducts having square or semi-circular cross sectional areas are tested in this work.
A developed numerical model for simulating the transported thermal energy in MSW is solved by finite difference method. The model is described by system of three governing energy equations. An experimental test rig has been built and six new duct configurations have b

The heat transfer and flow resistance characteristics for air flow cross over circular finned tube heat exchanger has been studied numerically and experimentally. The purpose of the study was to improve the heat transfer characteristics of an annular finned-tube heat exchanger for better performance. The study has concentrated on the effect of the number of perforations and perforations shapes on the heat transfer and pressure drop across a staggered finned tube heat exchanger. The Numerical part of present study has been performed using ANSYS Fluent 14.5 using SST Turbulent model, while the experimental study consist from a test rig with different models of heat exchangers and all required measurement devices were build

Metaheuristic is one of the most well-known fields of research used to find optimum solutions for non-deterministic polynomial hard (NP-hard) problems, for which it is difficult to find an optimal solution in a polynomial time. This paper introduces the metaheuristic-based algorithms and their classifications and non-deterministic polynomial hard problems. It also compares the performance of two metaheuristic-based algorithms (Elephant Herding Optimization algorithm and Tabu Search) to solve the Traveling Salesman Problem (TSP), which is one of the most known non-deterministic polynomial hard problems and widely used in the performance evaluations for different metaheuristics-based optimization algorithms. The experimental results of Ele

     In this paper, one of the Machine Scheduling Problems is studied, which is the problem of scheduling a number of products (n-jobs) on one (single) machine with the multi-criteria objective function. These functions are (completion time, the tardiness, the earliness, and the late work) which formulated as . The branch and bound (BAB) method are used as the main method for solving the problem, where four upper bounds and one lower bound are proposed and a number of dominance rules are considered to reduce the number of branches in the search tree. The genetic algorithm (GA) and the particle swarm optimization (PSO) are used to obtain two of the upper bounds. The computational results are calculated by coding (progr

In the present paper, three reliable iterative methods are given and implemented to solve the 1D, 2D and 3D Fisher’s equation. Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM) and Banach contraction method (BCM) are applied to get the exact and numerical solutions for Fisher's equations. The reliable iterative methods are characterized by many advantages, such as being free of derivatives, overcoming the difficulty arising when calculating the Adomian polynomial boundaries to deal with nonlinear terms in the Adomian decomposition method (ADM), does not request to calculate Lagrange multiplier as in the Variational iteration method (VIM) and there is no need to create a homotopy like in the Homotopy perturbation method (H

Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

 The aim of this paper is to present a semi - analytic technique for solving singular initial value problems of ordinary differential equations with a singularity of different kinds to construct polynomial solution using two point  osculatory  interpolation.           The efficiency and accuracy of suggested method is assessed by comparisons with exact and other approximate solutions for a wide classes of non–homogeneous, non–linear singular initial value problems.             A new, efficient estimate of the global error is used for adaptive mesh selection. Also, analyze some of the numerical aspects