The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods.
The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for
... Show MoreSeveral attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope
... Show MoreThis research aims at calculating the optimum cutting condition for various types of machining methods, assisted by computers, (the computer program in this research is designed to solve linear programs; the program is written in v. basic language). The program obtains the results automatically, this occur through entering the preliminary information about the work piece and the operating condition, the program makes the calculation actually by solving a group of experimental relations, depending on the type of machining method (turning, milling, drilling). The program was transferred to package and group of windows to facilitate the use; it will automatically print the initial input and optimal solution, and thus reduce the effort and t
... Show MoreMolasse medium containing different concentrations of (NH4)2 SO4, (NH4)3 PO4, urea, KCI, and P2O5 were compared with the medium used for commercial production of C. utilis in a factory south of Iraq. An efficient medium, which produced 19. 16% dry wt. and 5. 78% protein, was developed. The effect of adding various concentrations of micronutrients (FeSO4, 7T20, MnSO4. 7H20, ZnSO4. 7E20) was also studied. Results showed that FeSo4. 7H20 caused a noticeable increase in both dry wt. and protein content of the yeast.
Extended utilization of adaptive algorithms, Evaluative Algorithms (EAs), to address these issues offers a way to handle massive multi-objective optimization, even if the algorithmic method for handling combinations of objectives (CO) has been accessible for quite some time. Combining the idea of superiority with the Hypervolume (HV) tag approach, the GSA algorithm utilizes various target effects to explain several algorithms depending on the Hypervolume (HV) spacing. The Multi-objective Gravitational Search Algorithm with Hypervolume (MOGSA/HV). Since rapid convergence could result from GSA foundation work, Hypervolume rewrites the multi-objective problem (MOP) as a sequence of Tchebycheff solutions, improving it. Since the one in charge h
... Show MoreConstruction contractors usually undertake multiple construction projects simultaneously. Such a situation involves sharing different types of resources, including monetary, equipment, and manpower, which may become a major challenge in many cases. In this study, the financial aspects of working on multiple projects at a time are addressed and investigated. The study considers dealing with financial shortages by proposing a multi-project scheduling optimization model for profit maximization, while minimizing the total project duration. Optimization genetic algorithm and finance-based scheduling are used to produce feasible schedules that balance the finance of activities at any time w
Colloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO3 (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be
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