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An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem
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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 optimal timetable schedules with different copies by increasing the probability of giving the best schedule for each stage in the campus with the ability to replace the timetable when needed. The Evolutionary Algorithm (EA) utilized in this paper is the Genetic Algorithm (GA) which is a common multi-solution metaheuristic search based on the evolutionary population that can be applied to solve complex combinatorial problems like timetabling problems. In this work, all inputs: courses, teachers, and time acted by one array to achieve local search and combined this acting of the timetable by using the heuristic crossover to ensure that the essential conditions are not broken. The result of this work is a flexible scheduling system, which shows the diversity of all possible timetables that can be created depending on user conditions and needs.

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Intelligent Systems
An efficient node selection algorithm in the context of IoT-based vehicular ad hoc network for emergency service
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Abstract<p>With the recent growth of global populations, main roads in cities have witnessed an evident increase in the number of vehicles. This has led to unprecedented challenges for authorities in managing the traffic of ambulance vehicles to provide medical services in emergency cases. Despite the high technologies associated with medical tracks and advanced traffic management systems, there is still a current delay in ambulances’ attendance in times of emergency to provide patients with vital aid. Therefore, it is indispensable to introduce a new emergency service system that enables the ambulance to reach the patient in the least congested and shortest paths. However, designing an effici</p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving the Falkner-Skan Equation
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Publication Date
Fri Nov 01 2013
Journal Name
Al-nahrain Journal Of Science
Modified third order iterative method for solving nonlinear equations
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Many numerical approaches have been suggested to solve nonlinear problems. In this paper, we suggest a new two-step iterative method for solving nonlinear equations. This iterative method has cubic convergence. Several numerical examples to illustrate the efficiency of this method by Comparison with other similar methods is given.

Publication Date
Sat Oct 01 2016
Journal Name
International Journal Of Pure And Apllied Mathematics
A SEMI ANALYTICAL ITERATIVE TECHNIQUE FOR SOLVING DUFFING EQUATIONS
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Modern Mathematical Sciences
Coupled Laplace-Decomposition Method for Solving Klein- Gordon Equation
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In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
New Approach for Solving (1+1)-Dimensional Differential Equation
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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of King Saud University - Science
A semi-analytical iterative technique for solving chemistry problems
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Publication Date
Thu Jun 29 2023
Journal Name
Wasit Journal For Pure Sciences
Suitable Methods for Solving COVID-19 Model in Iraq
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Runge-kutta Numerical Method for Solving Nonlinear Influenza Model
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Abstract<p>The main object of this study is to solve a system of nonlinear ordinary differential equations (ODE) of the first order governing the epidemic model using numerical methods. The application under study is a mathematical epidemic model which is the influenza model at Australia in 1919. Runge-kutta methods of order 4 and of order 45 for solving this initial value problem(IVP) problem have been used. Finally, the results obtained have been discussed tabularly and graphically.</p>
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
The Operational Matrices Methods for Solving Falkner-Skan Equations
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     The method of operational matrices is based on the Bernoulli and Shifted Legendre polynomials which is used to solve the Falkner-Skan equation. The nonlinear differential equation converting to a system of nonlinear equations is solved using Mathematica®12, and the approximate solutions are obtained. The efficiency of these methods was studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as  increases. Moreover, the obtained approximate solutions are compared with the numerical solution obtained by the fourth-order Runge-Kutta method (RK4), which gives  a good agreement.

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