The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

Among a variety of approaches introduced in the literature to establish duality theory, Fenchel duality was of great importance in convex analysis and optimization. In this paper we establish some conditions to obtain classical strong Fenchel duality for evenly convex optimization problems defined in infinite dimensional spaces. The objective function of the primal problem is a family of (possible) infinite even convex functions. The strong duality conditions we present are based on the consideration of the epigraphs of the c-conjugate of the dual objective functions and the ε-c-subdifferential of the primal objective functions.

We wanted to find out how selenium (Se) affects broiler chicken performance, meat physicochemical properties, and selenium deposition in the tissues of broilers. Each of the 96 experimental pens had 30 chickens and included a total of 2,880 one-day-old broilers (Cobb 500 strain). A factorial design of four-by-three (SY + SS) and eight replicates (SY + SS) was used for the 12 experimental treatments, with selenium levels ranging from 0.15 to 0.60 ppm and organic (SY) or inorganic (SS) sources of selenium and their relationship (SY + SS). There were no differences in performance (P > 0.05) across Se levels or sources. 106 g/day of ADFI, 63 g/day of ADG, and 1.6844 kg/kg of FCR were found to be the averaging values for these three parameters:

The work of this paper is an investigation to improve the condenser performance of the automobile air conditioning system by enhancing the air-side heat transfer from the condenser through the use of an air guide net installed in front of the condenser face which is basically an aluminum plate having a circular entrance shape for the air passage.  The A/C system was examined under two types of test. The first test was conducted the air guide net, while the second was done with the air guide net. The performances of the A/C system under these tests were compared. For the second type of test, the experiment was carried out with three different size of air guide net, three different circular diameters (2, 3 and 3.5 cm) a

A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)

Sliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control

The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake