With increasing population and development, the resources of fossil fuels decreased, leading to the need to find alternative sources of energy. Furthermore, the use of fossil fuels is accompanied by several downsides including environmental fatality associated with toxic gas emissions from diesel engines and continuous increase of the price of diesel fuel. Biodiesel is one of the most important types of renewable energy that replaces the fossil fuel requirement (mineral diesel) and maintains eco-friendly sustainability. Calcium is an essential plant nutrient as it plays an important role in the formation of plant cell walls and membranes. Therefore, the fallen leaves of mango tree can be utilized to produce nano calcium oxide a

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

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

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.

The Traveling Salesman Problem is a story application of Atom Swarm Optimizations in this research. We have developed several novel techniques intended for solving TSP with PSO. Additionally, we introduced the notions to Swap Operative and Swap Chronological sequence and redefining the remaining operatives their foundation; that way, the study created unique PSO. Research prove it can produce satisfactory outcomes. The aim of this paper be there to assess the functioning of particle swarm optimization, for the going salesman issue TSP. The solution to this trouble is common to be NP-hard, it has N! permutations. The study's goal is to examine the capacity of both algorithms to solve intercontinental and other benchmark problems. Overall, th

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

Non-thermal plasmas have become popular as plasma technology has advanced in various fields, including waste management, aerospace technology, and medicinal applications. They can be used to replace combustion fuels in stationary hall motors and need little effort to keep running for longer periods of time. To improve overall system performance, non-reactive gases such as )Xe, Ar, and Kr) are utilized in pure or mixed form to generate plasma. Since DC glow discharge is a fundamental topic of importance, these gases have been researched. The paper concentrates on 2-D modeling and simulation. DC glow-discharge tubes are utilized with argon gas to create plasma and learn about its properties. The magnitude of the electron density, increases wi