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The demand for electricity supply increases day by day due to the rapid growth in the number of industries and consumer devices. The electric power supply needs to be improved by properly arranging distributed generators (DGs). The purpose of this paper is to develop a methodology for optimum placement of DGs using novel algorithms that leads to loss minimization.

In this paper, a novel hybrid optimization is proposed to minimize the losses and improve the voltage profile. The hybridization of the optimization is done through the crow search (CS) algorithm and the black widow (BW) algorithm. The CS algorithm is used for finding some tie-line systems, DG locations, and the BW algorithm is used for finding the rest of the tie-line switches, DG sizes, unlike in usual hybrid optimization techniques.

The proposed technique is tested on two large-scale radial distribution networks (RDNs), like the 119-bus radial distribution system (RDS) and the 135 RDS, and compared with normal hybrid algorithms.

The main novelty of this hybridization is that it shares the parameters of the objective function. The losses of the RDN can be minimized by reconfiguration and incorporating compensating devices like DGs.

The purpose of this paper is to track the maximal power of wind energy conversion system (WECS) and enhance the search capability for WECS maximum power point tracking (MPPT).

The hybrid technique is the combination of tunicate swarm algorithm (TSA) and radial basis function neural network.

TSA gets input parameters from the rectifier outputs such as rectifier direct current (DC) voltage, DC current and time. From the input parameters, it enhances the reduced fault power of rectifier and generates training data set based on the MPPT conditions. The training data set is used in radial basis function. During the execution time, it produces the rectifier reference DC side voltage that is converted to control pulses of inverter switches.

Finally, the proposed method is executed in MATLAB/Simulink site, and the performance is compared with different existing methods like particle swarm optimization algorithm and hill climb searching technique. Then the output illustrates the performance of the proposed method and confirms its capability to solve issues.

This paper aims to describe the use of optimization approaches to increase the range of near-future howitzer ammunition.

The performance of a gliding projectile concept is assessed using an aeroballistic workflow, comprising aerodynamic characterization and flight trajectory computation. First, a single-objective optimization is run with genetic algorithms to find the maximal attainable range for this type of projectile. Then, a multi-objective formulation of the problem is proposed to consider the compromise between range and time of flight. Finally, the aerodynamic model used for the gliding ammunition is evaluated, in comparison with direct computational fluid dynamics (CFD) computations.

Applying single-objective range maximization results in a great improvement of the reachable distance of the projectile, at the expense of the flight duration. Therefore, a multi-objective optimization is implemented in a second time, to search sets of parameters resulting in an optimal compromise between fire range and flight time. The resulting Pareto front can be directly interpreted and has the advantage of being useful for tactical decisions.

The main limitation of the work concerns the aerodynamic model of the gliding ammunition, which was initially proposed as an alternative to reduce significantly the computational cost of aerodynamic characterization and enable optimizations. When compared with direct CFD computations, this method appears to induce an overestimation of the range. This suggests future evolution to improve the accuracy of this approach.

To the best of the authors’ knowledge, this paper presents an original ammunition concept for howitzers, aiming at extending the range of fire by using lifting surfaces and guidance. In addition, optimization techniques are used to improve the range of such projectile configuration.

Cracking, deformation and rutting are the most prevalent types of pavement distress, and these deformations and flow characteristics greatly distress the pavement features while also limiting its use. In India, on the other hand, more than 300 million scrap tyres are generated each year, and their disposal has become a severe environmental issue. Furthermore, the scrap generated by the used tyre must be disposed of properly. Hence, this study presents the experimental investigations of bitumen incorporating with Crumb rubber as main additive along with SBS polymer, to enhance the engineering property.

Crumb rubber (CR) was used as an additive along with styrene–butadiene–styrene (SBS) polymer to enrich the engineering qualities of the bitumen to reduce the disposal problem of scrap tyres and reduce the risk of environmental pollution. Because SBS polymer is expensive, response surface methodology modelling's central composite design (CCD) was used to optimise the number of tests. CCD modelling's input factors (process variables) were the inclusion rates of SBS and CR, which ranged from 2% to 5% and 4% to 10%, respectively, by total weight. Furthermore, the influence of SBS polymer and CR on the characteristics of modified bitumen was prioritised.

The addition of SBS and CR enhanced the bitumen's penetration resistance at service temperatures. Furthermore, increasing the SBS and CR concentration affected the flow characteristics of the modified bitumen and enhanced its viscosity. The addition of SBS and CR as bitumen modifiers increased penetration resistance by 24.06%. The Dynamic Shear Rheometer test demonstrated that the complex modulus of virgin bitumen increases with increasing SBS and CR content, which is consistent with the shifting softening point trend. The dosing rate of up to 3.5% SBS and 11% CR considerably contributed to the creation of polymer link networks, which increased the complex modulus of the bitumen by 16.5%. The CCD model's analysis of variance and Pareto bar chart demonstrated that the dose of CR is significant in improving the engineering features of the virgin bitumen rather than the SBS.

The utilisation of CR as a bitumen modifier may solve the problem of waste tyre disposal while also lowering the risk of environmental damage. Furthermore, because the presence of CR increased the engineering properties, particularly the complex modulus of virgin bitumen, the use of CR in combination with SBS polymer can be an efficient and cost-effective strategy to improving bitumen qualities.