Top Research Papers on Optimization Techniques

Flavonoids, specialized metabolites found in plants, have a number of beneficial properties and are important for maintaining good health. Efficient extraction methods are required to extract the most bioactive compounds from plant material. Modern techniques are replacing conventional methods of flavonoids extraction in order to reduce energy and solvent consumption, increase extraction efficiency, and satisfy growing market demand as well as environmental legislation. The extraction of bioactive molecules compounds is affected by a number of variables. To determine the conditions that ensure...

This paper presents a comprehensive survey of techniques for optimizing the inference phase of transformer networks, and surveys techniques such as knowledge distillation, pruning, quantization, neural architecture search and lightweight network design at the algorithmic level.

This survey discusses various optimization techniques found in 450 articles published in the last 14 years and shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.

The objective of this paper, is to share the clock tree optimization techniques and the result of the optimization techniques, from timing, power and skew aspects, that will benefit the design community in clock optimization solutions.

This paper presents a multi-objective version of the Cat Swarm Optimization Algorithm called the Grid-based Multi-objective Cat Swarm Optimization Algorithm (GMOCSO), which replaces the roulette wheel method of the original CSO algorithm with a greedy method and adopts two key concepts from Pareto Archived Evolution Strategy Algorithm (PAES).

Two recent meta-heuristic approaches are introduced, the BA and ALOA: a rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA and a bat algorithm which is suitable for economic dispatch studies.

It is determined it is unclear which optimization approach (CVaR or Robust MVO) leads to better crypto portfolios, and so, to address this, optimization procedures on out-of-sample data are compared through a thorough cross-validation of hyperparameters for each technique.

A new design of a milling tool with a weight reduced by 30% is presented; SLM process has been selected to realize the millingtool and the new geometry has been little modified.

Different optimization algorithms for reducing the side lobe level of the antenna array are presented and various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed.

A network-based method to identify the most influential nodes by combining network centrality and optimization is proposed, demonstrating that various network properties, such as between and degree centralities, influence the priorities of nodes as targets, and that using an optimization model yields better priorities with decreasing marginal properties.

A novel way for EV charging is presented by establishing a smart charging hub network using dynamic K-means clustering and a synchronized hub network that employs a novel clustering method, organizes charging nodes, predicts demand via predictive analytics, employs RES, and encourages consumers to use environmentally conscious charging behaviours.

In the current work, a modified version of the Simulated Annealing algorithm is used as a local optimization procedure in Grammatical Evolution and a remarkable improvement of the experimental results was shown, both in classification data and in data fitting cases.

The results indicate that the proposed method is effective in achieving the accuracy and works well with the state-of-the-art architectures.

The suitable conditions for applying optimization techniques to search for optimal reservoir rule curves to be effectively applied in future reservoir operations are presented.

An unique picture encryption technique based on a chaotic map and DNA encoding is jointly used for image encryption in a more pragmatic approach, as necessary in today’s world to safeguard private data.

This paper presents an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques.

The current state-of-the-art optimization techniques for designing the scaffolds and the settings of different optimization methods are introduced and various design methods for bone scaffolds are reviewed.

This study proposes a new technique for linearizing the square root terms by means of transformation, which is anticipated to reveal some important insights to researchers and practitioners, who are closely working with non-linear optimization models, and assist with effective decision making.

This paper is to dig deep and describe all kinds of model optimization at different levels and layers and highlighted the importance of having an enabling AI model optimization framework.

This review paper discusses microgrid and home energy management, demand-side management, unit commitment, microgrid integration, and economic dispatch as examples of applications of probabilistic optimization techniques in smart power systems.

The optimization strategy proposed in this paper correctly reconstructs the parallel regions and reduces its execution overhead; it reduces the number of redundant synchronizations and effectively improve the performance of OpenMP program.

The Newton-Raphson (NR) load flow method is used for IEEE 14 bus with its standard bus and branch data and the optimal size and location of G-UPFC found out by using ant colony optimization (ACO) is inserted in the different IEEE bus systems.

The proposed L2O-ILT framework unrolls the iterative ILT optimization algorithm into a learnable neural network with high interpretability, which can generate a high-quality initial mask for fast refinement.

The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operati...

The modern period has seen advancements in compiler design, optimization technique, and software system efficiency, and the design of the compiler is advanced by the efficient code now structured in research with high-speed performance without manual intervention.

This paper investigates various algorithms and optimizers based on these which are used for rectenna optimization and finds the optimal values of passive components used in the design.

This study compares the effectiveness of various machine-learning algorithms and optimization techniques, and it suggests a novel machine- learning strategy paired with optimization algorithms for car price prediction that would be made simpler and more adaptable by applying machine learning techniques to the issue.

A range of SQL Server optimization techniques that can significantly enhance database performance are examined, including effective indexing, which improves query execution speed; query optimization, which refines SQL statements for better efficiency; and proper database configuration, which ensures that SQL Server is tuned for optimal resource utilization.

A comparative study to test and evaluate the performance of three algorithms: Simulated Annealing, Ant Colony Optimization, and Genetic Algorithm by setting up analogous environments of n cities.

It is proved that the proposed Adaptive-JAYA approach improves the output power by 26.12%, 22.20%, 7.61%, and 7.68% compared to the TCT for the four shading patterns, i.e. SW, LW, SN, and LN.

A survey on the state-of-the-art network structures and communication mechanisms used in blockchain and the need for network-based optimization is provided and recommendations for future work are presented.

The work proposes the Autonomous Groups Particle Swarm Optimization (AGPSO) approach for the optimal placement and sizing of the Static Var Compensator (SVC) to minimize the total active power losses in transmission lines.

Process Intensification (PI) is a vast and growing area in Chemical Engineering, which deals with the enhancement of current technology to enable improved efficiency; energy, cost, and environmental impact reduction; small size; and better integration with the other equipment. Since process intensification results in novel, but complex, systems, it is necessary to rely on optimization and control techniques that can cope with such new processes. Therefore, this review presents some advancements in the field of process intensification that are worthy of exploring in detail in the coming years. ...

The paper presents two approaches for destroying steganogrphy content in an image, the overwriting approach where a random data can be written again over steganographic images whereas the second approach is the denoising approach, which enhances the PSNR in any received image even without hidden information.

This review paper provides a comprehensive examination of the applications of RL in the field of energy system optimization, spanning various domains such as energy management, grid control, and renewable energy integration.

The objectives of this paper are to discuss the most important optimization algorithms, classify the scientific fields involved in their application, and optimize problems involved in this regard, in addition to providing a brief overview for comparison among these algorithms.

Improved techniques for optimization-based jailbreaks like GCG are presented and demonstrated that they can help GCG outperform state-of-the-art jailbreaking attacks and achieve nearly 100% attack success rate.

The LEACH-CHIO is proposed, a centralized cluster-based energy-aware protocol based on the Coronavirus Herd Immunity Optimizer (CHIO) algorithm, a newly emerging human-based optimization algorithm that is expected to achieve significant improvement in the LEACH cluster heads selection process.

A survey of various initialization approaches implied in the PSO that are based on quasi-random sequences (Halton, Torus) and pseudo-random sequence (LCG, MCG) strategies and the efficiency of many QRS and PRNG based initialization approaches is found by comparing their performance observed for nine famous benchmark test problems.

This work describes the least-detectable trajectory that the elusive vessel can take, and proposes a globally-optimal and computationally-efficient technique, called the Non-Convex Optimized Stealth Trajectory (N-COST) algorithm.

This investigation demonstrated that GA, FA, BA, FPA, and TS associated with the reservoir simulation model could give the ideal principle bends which better moderate the drought and flood circumstances contrasted and current guideline bends.

This paper provided detailed knowledge of optimization, several approaches and their applications in civil engineering, i.e. structural, geotechnical, hydraulic, transportation and many more, where the lack of exploratory studies is to be approached soon.

This review article describes the main osteotomies performed around the knee and their optimization, with particular attention to indications and surgical technique in light of the most recent literature and author experience.

The gap analysis of optimization techniques used in medical image analysis with the possible future research direction is provided and the contribution of optimization‐based medical image classification and segmentation utilized image modalities, data sets, and tradeoffs are discussed.

There is a huge trend to use intelligence-based routing in programmable networks, particularly during the last three years, but a lot of effort is still required to achieve comprehensive comparisons and synergies of approaches, meaningful evaluations based on open datasets and topologies, and detailed practical implementations that could be adopted by industry.

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The newly proposed Grey Wolf Optimization (GWO) algorithm is used in this paper to design a linear-phase FIR filter to obtain the optimal transition-band sample value in the frequency sampling method to obtaining the minimum stop-band attenuation, so as to improve the performance of the filter.

Findings of the effectiveness of online presentations are reviewed and recommendations on how to enhance the online learner's ability to engage by using pre-performance routines or habits are made.

This research introduces the Iterative Overlap Optimization Placement (IOOP) method, a novel approach designed to enhance the efficiency of irregular pattern packing by dynamically optimizing overlap ratios and pattern placements. Utilizing a modified genetic algorithm, IOOP addresses the complexities of arranging irregular patterns in a given space, focusing on improving spatial and material efficiency. This study demonstrates the method’s superiority over the traditional Size-First Non-Iterative Overlap Optimization Placement technique through comparative analysis, highlighting significant i...

The efficiency and sustainability of biodiesel manufacturing processes may be enhanced by machine learning, as demonstrated by the results derived from the best-fitted model.