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Journal articles on the topic 'I/O optimization'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Mukherjee, Manasij, and John Regehr. "Hydra: Generalizing Peephole Optimizations with Program Synthesis." Proceedings of the ACM on Programming Languages 8, OOPSLA1 (2024): 725–53. http://dx.doi.org/10.1145/3649837.

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Optimizing compilers rely on peephole optimizations to simplify combinations of instructions and remove redundant instructions. Typically, a new peephole optimization is added when a compiler developer notices an optimization opportunity---a collection of dependent instructions that can be improved---and manually derives a more general rewrite rule that optimizes not only the original code, but also other, similar collections of instructions. In this paper, we present Hydra, a tool that automates the process of generalizing peephole optimizations using a collection of techniques centered on pr

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Sartoros, Christine, Douglas M. Goltz, and Eric D. Salin. "Program Considerations for Simplex Optimization of Ion Lenses in ICP-MS." Applied Spectroscopy 52, no. 5 (1998): 643–48. http://dx.doi.org/10.1366/0003702981944292.

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The performance of an inductively coupled plasma mass spectrometer (ICP-MS) is dependent on the ion optic bias potentials. A discussion of the multielement optimization of the ICP-MS ion optics bias potentials using a Simplex algorithm is presented. Three objective functions were tested: a function developed by Leary; the combined ratio method (CRM); and the Euclidean distance from multicriteria target vector optimization. Both the Leary and the target vector optimization's performances were comparable, whereas the CRM optimizations placed an emphasis on obtaining similar signal intensities. E

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Nan, Yang. "An Improved Ant Colony Optimization Algorithm Based on Immunization Strategy." Advanced Materials Research 490-495 (March 2012): 66–70. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.66.

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Ant colony optimization has been become a very useful method for combination optimization problems. Based on close connections between combination optimization and continuous optimization, nowadays some scholars have studied to apply ant colony optimization to continuous optimization problems, and proposed some continuous ant colony optimizations. To improve the performance of those continuous ant colony optimizations, here the principles of evolutionary algorithm and artificial immune algorithm have been combined with the typical continuous Ant Colony Optimization, and the adaptive Cauchi mut

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Zhong, Mei Peng. "Parameter Optimization of Compressor Based on an Ant Colony Optimization." Applied Mechanics and Materials 201-202 (October 2012): 916–19. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.916.

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A mathematical model of operation on air compressors is set up in order to improve the efficiency of air compressors. Parameter of Compressor is optimized by an Ant Colony Optimization (ACO) Particle approach. Volume and its weight of the new compressor are little, and its efficiency is high. An Ant Colony Optimization embed BLDCM module which optimizating the air compressor was put forward. Optimizated target of an Ant Colony Optimization is the efficiency of BLDCM. Optimizated variables are the diameter of low pressure cylinder, the diameter of high pressure cylinder, the journey of low pres

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Rajeanderan Revichandran, Jaffar Syed Mohamed Ali, Moumen Idres, and A. K. M. Mohiuddin. "A Review of HVAC System Optimization and Its Effects on Saving Total Energy Utilization of a Building." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 93, no. 1 (2022): 64–82. http://dx.doi.org/10.37934/arfmts.93.1.6482.

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The paper illustrates the review on the optimizations studies of HVAC systems based on three main methods – HVAC operational variables optimization, optimization of control parameters in HVAC system and parameter optimization in building models. For the HVAC system’s operational variables, the optimization process is based on the common and prescient energy utilization models. Thus, by comparing both, the non-common HVAC system models can get better output of energy reduction. Based on most of the studies, the occupancies thermal comfort requirements, are represented by the indoor air quality

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Ren, Xiaolei, Mengfei Ren, Yu Lei, and Jiang Ming. "Revisiting Optimization-Resilience Claims in Binary Diffing Tools: Insights from LLVM Peephole Optimization Analysis." Proceedings of the ACM on Software Engineering 2, FSE (2025): 2689–711. https://doi.org/10.1145/3729389.

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Binary diffing technique aims to identify differences/similarities in executable files without source code access. Its potential applications in various software security tasks, such as vulnerability search, code clone detection, and malware analysis have generated a large body of literature over the past few years. A recurring theme in binary diffing research is to evaluate the resilience against the impact of compiler optimization, which is the most common source leading to syntactic differences in binary code. Despite claims by most binary diffing papers that they are immune to compiler opt

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Zhu, Mingxuan, Zeyu Sun, and Dan Hao. "PDCAT: Preference-Driven Compiler Auto-tuning." Proceedings of the ACM on Software Engineering 2, FSE (2025): 847–67. https://doi.org/10.1145/3715756.

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Compilers are crucial software tools that usually convert programs in high-level languages into machine code. A compiler provides hundreds of optimizations to improve the performance of the compiled code, which are controlled by enabled or disabled optimization flags. However, the vast number of combinations of these flags makes it extremely challenging to select the desired settings for compiler optimization flags (i.e., an optimization sequence) for a given target program. In the literature, many auto-tuning techniques have been proposed to select a desired optimization sequence via differen

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Batay, Sagidolla, Bagdaulet Kamalov, Dinmukhamed Zhangaskanov, et al. "Adjoint-Based High-Fidelity Concurrent Aerodynamic Design Optimization of Wind Turbine." Fluids 8, no. 3 (2023): 85. http://dx.doi.org/10.3390/fluids8030085.

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To evaluate novel turbine designs, the wind energy sector extensively depends on computational fluid dynamics (CFD). To use CFD in the design optimization process, where lower-fidelity approaches such as blade element momentum (BEM) are more popular, new tools to increase the accuracy must be developed as the latest wind turbines are larger and the aerodynamics and structural dynamics become more complex. In the present study, a new concurrent aerodynamic shape optimization approach towards multidisciplinary design optimization (MDO) that uses a Reynolds-averaged Navier–Stokes solver in conjun

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9

Seth, Ashish. "Regression Test Case Optimization Using Ant Colony Optimization." Journal of Advanced Research in Dynamical and Control Systems 12, no. 3 (2020): 111–18. http://dx.doi.org/10.5373/jardcs/v12i3/20201172.

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10

Prathyusha, Kosuru. "Performance Optimization in Web Applications." European Journal of Advances in Engineering and Technology 6, no. 8 (2019): 100–104. https://doi.org/10.5281/zenodo.13919484.

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Application performance optimization is an essential process that helps improve the usability of web applications. This document aims to discuss various ways of increasing both the front-end and back-end performance levels. It includes basic front-end optimizations such as lazy loading and caching and back-end optimizations including database indexing and query optimization. By using these methods, developers can increase the effectiveness of work and efficiency of web applications (Ahmed et al., 2016)

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Geller, Adam T., Sean Bocirnea, Chester J. F. Gould, Paulette Koronkevich, and William J. Bowman. "Type-Preserving Flat Closure Optimization." Proceedings of the ACM on Programming Languages 9, OOPSLA1 (2025): 649–75. https://doi.org/10.1145/3720437.

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Type-preserving compilation seeks to make intent as much as a part of compilation as computation. Specifications of intent in the form of types are preserved and exploited during compilation and linking, alongside the mere computation of a program. This provides lightweight guarantees for compilation, optimization, and linking. Unfortunately, type-preserving compilation typically interferes with important optimizations. In this paper, we study typed closure representation and optimization. We analyze limitations in prior typed closure conversion representations, and the requirements of many im

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Zhang, Laiyong, Chunming Tu, Fan Xiao, Bei Liu, and Peiqiang Li. "Intrinsic Regularity Analysis and Optimization Control of Current Stress and RMS for Dual-Active Bridge Converter." Electronics 13, no. 23 (2024): 4802. https://doi.org/10.3390/electronics13234802.

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Currently, current stress optimization control and current effective value optimization control have become the mainstream methods for real-time optimization control of dual-active bridge converters. However, there is still a lack of systematic research on the internal optimization regularities between the two and their respective internal optimization regularities, as well as problems such as the complex derivation of the effective value optimization control variable function. To address these issues, this paper analyzes the optimization results of stress optimization, effective value optimiz

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Celik, Yuksel, and Erkan Ulker. "An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization." Scientific World Journal 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/370172.

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Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm’s performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

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Masarik, Jozef. "A thermodynamically motivated optimization algorithm: Circular wheel balance optimization." Applications of Mathematics 30, no. 6 (1985): 413–24. http://dx.doi.org/10.21136/am.1985.104171.

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Xu, Liansong, and Dazhi Pan. "Multi-objective Optimization Based on Chaotic Particle Swarm Optimization." International Journal of Machine Learning and Computing 8, no. 3 (2018): 229–35. http://dx.doi.org/10.18178/ijmlc.2018.8.3.692.

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Satoh, Shigehisa, Kazuhiro Kusano, and Mitsuhisa Sato. "Compiler Optimization Techniques for OpenMP Programs." Scientific Programming 9, no. 2-3 (2001): 131–42. http://dx.doi.org/10.1155/2001/189054.

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We have developed compiler optimization techniques for explicit parallel programs using the OpenMP API. To enable optimization across threads, we designed dataflow analysis techniques in which interactions between threads are effectively modeled. Structured description of parallelism and relaxed memory consistency in OpenMP make the analyses effective and efficient. We developed algorithms for reaching definitions analysis, memory synchronization analysis, and cross-loop data dependence analysis for parallel loops. Our primary target is compiler-directed software distributed shared memory syst

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17

Klimczyk, Witold Artur, and Zdobyslaw Jan Goraj. "Robust design and optimization of UAV empennage." Aircraft Engineering and Aerospace Technology 89, no. 4 (2017): 609–19. http://dx.doi.org/10.1108/aeat-11-2016-0221.

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Purpose This paper aims to address the issue of designing aerodynamically robust empennage. Aircraft design optimization often narrowed to analysis of cruise conditions does not take into account other flight phases (manoeuvres). These, especially in unmanned air vehicle sector, can be significant part of the whole flight. Empennage is a part of the aircraft, with crucial function for manoeuvres. It is important to consider robustness for highest performance. Design/methodology/approach Methodology for robust wing design is presented. Surrogate modelling using kriging is used to reduce the opt

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18

Zhang, Zhengfang, Weifeng Chen, and Xiaoliang Cheng. "A Penalty Optimization Algorithm for Eigenmode Optimization Problem Using Sensitivity Analysis." Communications in Computational Physics 15, no. 3 (2014): 776–96. http://dx.doi.org/10.4208/cicp.190313.090913a.

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AbstractThis paper investigates the eigenmode optimization problem governed by the scalar Helmholtz equation in continuum system in which the computed eigenmode approaches the prescribed eigenmode in the whole domain. The first variation for the eigenmode optimization problem is evaluated by the quadratic penalty method, the adjoint variable method, and the formula based on sensitivity analysis. A penalty optimization algorithm is proposed, in which the density evolution is accomplished by introducing an artificial time term and solving an additional ordinary differential equation. The validit

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Hegazy, Tarek, and Ahmed Elhakeem. "Multiple optimization and segmentation technique (MOST) for large-scale bilevel life cycle optimization." Canadian Journal of Civil Engineering 38, no. 3 (2011): 263–71. http://dx.doi.org/10.1139/l10-134.

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This paper introduces a new formulation for large-scale combinatorial bilevel optimization problems that involve integer, discrete, two-level decisions. The most vivid example where the new technique most applies is the life cycle optimization needed to allocate repair types and repair timings to a number of infrastructure assets (e.g., building components). Combining these decisions into a single optimization for hundreds of assets simultaneously makes the optimization problem complex and prohibitive. For such a large-scale problem, a multiple optimization and segmentation technique (MOST) is

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Mueller, Carsten. "Multi-Objective Optimization of Software Architectures Using Ant Colony Optimization." Lecture Notes on Software Engineering 2, no. 4 (2014): 371–74. http://dx.doi.org/10.7763/lnse.2014.v2.152.

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21

Lee, Youngmyung, Yong-Ha Han, Sang-ok Park, and Gyung-Jin Park. "Vehicle crash optimization considering a roof crush test and a side impact test." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 10 (2018): 2455–66. http://dx.doi.org/10.1177/0954407018794259.

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The vehicle performances for the side impact test and the roof crush test are dependent on the side structure design of a vehicle. Crash optimization can be employed to enhance the performances. A meta-model-based structural optimization technique is generally utilized in the optimization process since the technique is simple to use. However, the meta-model-based optimization is not suitable for problems with many design variables such as topology and topometry optimizations. A crash optimization methodology is proposed to consider both the side impact test and the roof crush test. The equival

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22

Sumarno, Radiktyo Nindyo, Susatyo Handoko, and Mochammad Facta. "The Improvement of Electric Power Losses Using Bank Capacitor and Tap Changer With Shark Smell Algorithm." TEKNIK 41, no. 3 (2020): 212–18. http://dx.doi.org/10.14710/teknik.v41i3.24818.

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One way to optimize the transmission line is to reduce electrical power losses. Tap changers on power transformers and bank capacitors can be used to regulate the system voltage resulting in lower power losses in the transmission line. Determining the value of tap settings and bank capacitors in the planning process is challenging to do with certainty. It is generally carried out through a trial and error mechanism using the power flow method. Since the determination of tap settings and bank capacitors values is difficult to do with certainty, this research was carried out with optimization wi

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23

Gu, Xiaoyu, John E. Renaud, Leah M. Ashe, Stephen M. Batill, Amrjit S. Budhiraja, and Lee J. Krajewski. "Decision-Based Collaborative Optimization." Journal of Mechanical Design 124, no. 1 (2000): 1–13. http://dx.doi.org/10.1115/1.1432991.

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In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg [1,2] is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a

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Zhang, Zhuo Qun, and Hong Nan Li. "Two-Level Optimization Method of Transmission Tower Structure Based on Ant Colony Algorithm." Advanced Materials Research 243-249 (May 2011): 5849–53. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5849.

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This paper highlights a two-level optimization process combined with ant colony optimization algorithm (ACO)，which is applied to design the shape of the transmission tower structure, and compiles optimization design procedure for the solution of the structure shape with the MATLAB language. By comparing the different methods of the transmission tower structure optimization design, the ACO algorithm is demonstrated to be more accuracy and practical in dealing the complex optimizations problem, i.e. the combination of continuous variables and discrete variables. These calculation examples illust

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Tao, Ziyou. "Stress Analysis and Size Optimization of Suspension Beam Structure of Robot Manipulator." Theoretical and Natural Science 2, no. 1 (2023): 92–96. http://dx.doi.org/10.54254/2753-8818/2/20220174.

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In this paper, the stress and deformation of a manipulator structure are analyzed, and the structural optimization design is carried out. The initial configuration is a cantilever beam structure with rectangular section, which is fixed at one end and bears a load of 1 ton at the other end. After stress and deformation analysis with ABAQUS software and SolidWorks software, three optimizations were carried out. Geometric configuration optimization, topology optimization and material optimization. After optimization, the overall quality of the structure is reduced by 80%, and there is no great lo

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Phommixay, Sengthavy, Mamadou Lamine Doumbia, and David Lupien St-Pierre. "Review on the cost optimization of microgrids via particle swarm optimization." International Journal of Energy and Environmental Engineering 11, no. 1 (2019): 73–89. http://dx.doi.org/10.1007/s40095-019-00332-1.

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AbstractEconomic analysis is an important tool in evaluating the performances of microgrid (MG) operations and sizing. Optimization techniques are required for operating and sizing an MG as economically as possible. Various optimization approaches are applied to MGs, which include classic and artificial intelligence techniques. Particle swarm optimization (PSO) is one of the most frequently used methods for cost optimization due to its high performance and flexibility. PSO has various versions and can be combined with other intelligent methods to realize improved performance optimization. This

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Bendsoe, Martin P. "Multidisciplinary Topology Optimization." Proceedings of The Computational Mechanics Conference 2006.19 (2006): 1. http://dx.doi.org/10.1299/jsmecmd.2006.19.1.

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Wu, Qingkun, Lingen Chen, Yanlin Ge, and Huijun Feng. "Four-Objective Optimization of an Irreversible Magnetohydrodynamic Cycle." Entropy 24, no. 10 (2022): 1470. http://dx.doi.org/10.3390/e24101470.

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Based on the existing model of an irreversible magnetohydrodynamic cycle, this paper uses finite time thermodynamic theory and multi-objective genetic algorithm (NSGA-II), introduces heat exchanger thermal conductance distribution and isentropic temperature ratio of working fluid as optimization variables, and takes power output, efficiency, ecological function, and power density as objective functions to carry out multi-objective optimization with different objective function combinations, and contrast optimization results with three decision-making approaches of LINMAP, TOPSIS, and Shannon E

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Xu, Haoran, Lingen Chen, Yanlin Ge, and Huijun Feng. "Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law." Entropy 24, no. 10 (2022): 1491. http://dx.doi.org/10.3390/e24101491.

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This paper combines the mechanical efficiency theory and finite time thermodynamic theory to perform optimization on an irreversible Stirling heat-engine cycle, in which heat transfer between working fluid and heat reservoir obeys linear phenomenological heat-transfer law. There are mechanical losses, as well as heat leakage, thermal resistance, and regeneration loss. We treated temperature ratio x of working fluid and volume compression ratio λ as optimization variables, and used the NSGA-II algorithm to carry out multi-objective optimization on four optimization objectives, namely, dimension

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Huang, Daniel, Junwei Lucas Bao, and Jean-Baptiste Tristan. "Geometry meta-optimization." Journal of Chemical Physics 156, no. 13 (2022): 134109. http://dx.doi.org/10.1063/5.0087165.

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Recent work has demonstrated the promise of using machine-learned surrogates, in particular, Gaussian process (GP) surrogates, in reducing the number of electronic structure calculations (ESCs) needed to perform surrogate model based (SMB) geometry optimization. In this paper, we study geometry meta-optimization with GP surrogates where a SMB optimizer additionally learns from its past “experience” performing geometry optimization. To validate this idea, we start with the simplest setting where a geometry meta-optimizer learns from previous optimizations of the same molecule with different ini

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Xie, Hua Long, Hui Min Guo, Qing Bao Wang, and Yong Xian Liu. "The Spindle Structural Optimization Design of HTC3250µn NC Machine Tool Based on ANSYS." Advanced Materials Research 457-458 (January 2012): 60–64. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.60.

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The optimization of spindle has important significance. The optimization method based on ANSYS is introduced and spindle mathematical mode of HTC3250µn NC machine tool is given. By scanning of design variables, the main optimized design variables are determined. The single objective and multi-objective optimizations are done. In the end, the main size comparison of spindle before and after optimization is given.

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Liu, Yuanyuan, Shunguang Song, and Chunjie Wang. "Multi-objective optimization on the shock absorber design for the lunar probe using nondominated sorting genetic algorithm II." International Journal of Advanced Robotic Systems 14, no. 4 (2017): 172988141772046. http://dx.doi.org/10.1177/1729881417720467.

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In this article, the design on the shock absorber of the lunar probe soft landing can be considered as a single- or multi-objective optimization problem. Here, the optimized objective parameters include the maximum toppling stability, defined as Dmin, and the minimum stroke of primary strut energy absorption, SPmax. However, the two optimized variables are conflict objectives. In order to give an overall consideration about the multi-performances of landing, the multi-objective optimization strategy is proposed and nondominated sorting genetic algorithm II is employed to find the best decision

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He, Jinhu, Lingen Chen, Yanlin Ge, Shuangshuang Shi, and Fang Li. "Four-Objective Optimizations of a Single Resonance Energy Selective Electron Refrigerator." Entropy 24, no. 10 (2022): 1445. http://dx.doi.org/10.3390/e24101445.

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According to the established model of a single resonance energy selective electron refrigerator with heat leakage in the previous literature, this paper performs multi-objective optimization with finite-time thermodynamic theory and NSGA-II algorithm. Cooling load (R¯), coefficient of performance (ε), ecological function (ECO¯), and figure of merit (χ¯) of the ESER are taken as objective functions. Energy boundary (E′/kB) and resonance width (ΔE/kB) are regarded as optimization variables and their optimal intervals are obtained. The optimal solutions of quadru-, tri-, bi-, and single-objective

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Liu, Manqi. "Current Status, Development, And Application of Optimization Methods for Analog Circuits." Highlights in Science, Engineering and Technology 81 (January 26, 2024): 438–43. http://dx.doi.org/10.54097/j4vjfn83.

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The optimization of analog circuits has always relied on the experience and intuition of engineers to find suitable parameters to meet the requirements of the circuit, which is time-consuming and costly. This paper outlines and analyzes the optimization methods for analog circuits in recent years, and draws some summaries that can be used as references for subsequent optimization circuits. The optimization of analog circuits is mainly divided into the optimization of the performance of the hardware in the circuit and the optimization of the circuit structure. Hardware optimization, this paper

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Onaolapo, A. K., and B. T. Abe. "An Extensive Assessment of the Energy Management and Design of Battery Energy Storage in Renewable Energy Systems." WSEAS TRANSACTIONS ON POWER SYSTEMS 19 (May 9, 2024): 146–70. http://dx.doi.org/10.37394/232016.2024.19.17.

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Many benefits are derivable when renewable energy systems (RES) are integrated with battery energy storage systems (BESS). However, appropriate energy management techniques should be adopted to realize optimal benefits. Many BESS operations’ optimization approaches are available in RES with various techno-economic, environmental, and dispatch-related outputs. BESS operations are optimized using different methods. Past studies have mainly concentrated on certain renewable energy systems designed for specific purposes, such as distributed generation or large-scale. This paper thoroughly examines

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Vlahopoulos, N., and C. G. Hart. "A Multidisciplinary Design Optimization Approach to Relating Affordability and Performance in a Conceptual Submarine Design." Journal of Ship Production and Design 26, no. 04 (2010): 273–89. http://dx.doi.org/10.5957/jspd.2010.26.4.273.

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A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics

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Cui, Can, Bowen Wu, and Wen Huo. "Optimization of intake and exhaust structure of rotary engine based on active subspace method." Journal of Physics: Conference Series 3043, no. 1 (2025): 012138. https://doi.org/10.1088/1742-6596/3043/1/012138.

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Abstract The high dimensionality and computational complexity of traditional intake and exhaust system optimization methods for Wankel rotary engine (WRE) urgently require efficient optimization methods to improve computational efficiency. This paper optimizes the intake and exhaust system of a downsized WRE through the active subspace method. It collects the mapping between intake/exhaust parameters and power via simulation, fits the data with a global linear model, and reduces the optimization space from six dimensions to one through feature decomposition. Results show power decreases monoto

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Kwon, Jaeseong, Bongjun Jang, Juneyoung Lee, and Kihong Heo. "Optimization-Directed Compiler Fuzzing for Continuous Translation Validation." Proceedings of the ACM on Programming Languages 9, PLDI (2025): 627–50. https://doi.org/10.1145/3729275.

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Incorrect compiler optimizations can lead to unintended program behavior and security vulnerabilities. However, the enormous size and complexity of modern compilers make it challenging to ensure the correctness of optimizations. The problem becomes more severe as compiler engineers continuously add new optimizations to improve performance and support new language features. In this paper, we propose Optimuzz, a framework to effectively detect incorrect optimization bugs in such continuously changing compilers. The key idea is to combine two complementary techniques: directed grey-box fuzzing an

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Jia, Jia, and Dejun Mu. "Low-Energy-Orientated Resource Scheduling in Cloud Computing by Particle Swarm Optimization." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, no. 2 (2018): 339–44. http://dx.doi.org/10.1051/jnwpu/20183620339.

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In order to reduce the energy cost in cloud computing, this paper represents a novel energy-orientated resource scheduling method based on particle swarm optimization. The energy cost model in cloud computing environment is studied first. The optimization of energy cost is then considered as a multiobjective optimization problem, which generates the Pareto optimization set. To solve this multiobjective optimization problem, the particle swarm optimization is involved. The states of one particle consist of both the allocation plan for servers and the frequency plans on servers. Each particle in

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Wang, Chenxiao, Zach Arani, Le Gruenwald, Laurent d'Orazio, and Eleazar Leal. "Re-optimization for Multi-objective Cloud Database Query Processing using Machine Learning." International Journal of Database Management Systems 13, no. 1 (2021): 21–40. http://dx.doi.org/10.5121/ijdms.2021.13102.

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In cloud environments, hardware configurations, data usage, and workload allocations are continuously changing. These changes make it difficult for the query optimizer of a cloud database management system (DBMS) to select an optimal query execution plan (QEP). In order to optimize a query with a more accurate cost estimation, performing query re-optimizations during the query execution has been proposed in the literature. However, some of there-optimizations may not provide any performance gain in terms of query response time or monetary costs, which are the two optimization objectives for cl

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Gireesha. B, Mr, and . "A Literature Survey on Artificial Swarm Intelligence based Optimization Techniques." International Journal of Engineering & Technology 7, no. 4.5 (2018): 455. http://dx.doi.org/10.14419/ijet.v7i4.5.20205.

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From few decades’ optimizations techniques plays a key role in engineering and technological field applications. They are known for their behaviour pattern for solving modern engineering problems. Among various optimization techniques, heuristic and meta-heuristic algorithms proved to be efficient. In this paper, an effort is made to address techniques that are commonly used in engineering applications. This paper presents a basic overview of such optimization algorithms namely Artificial Bee Colony (ABC) Algorithm, Ant Colony Optimization (ACO) Algorithm, Fire-fly Algorithm (FFA) and Particle

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Yepes, Víctor, José V. Martí, and José García. "Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls." Sustainability 12, no. 7 (2020): 2767. http://dx.doi.org/10.3390/su12072767.

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The optimization of the cost and CO 2 emissions in earth-retaining walls is of relevance, since these structures are often used in civil engineering. The optimization of costs is essential for the competitiveness of the construction company, and the optimization of emissions is relevant in the environmental impact of construction. To address the optimization, black hole metaheuristics were used, along with a discretization mechanism based on min–max normalization. The stability of the algorithm was evaluated with respect to the solutions obtained; the steel and concrete values obtained in both

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Brekalo, Sanja, Klaudio Pap, and Bruno Trstenjak. "Enhancing Rendering Performance in Complex Visualizations by using Optimization Techniques and Algorithms in Browser Environments." Engineering, Technology & Applied Science Research 14, no. 3 (2024): 14049–55. http://dx.doi.org/10.48084/etasr.7201.

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This research is based on the hypothesis that optimization techniques can significantly improve the performance of complex visualizations in web browsers. The aim of the former was to determine to which extent the optimization can be achieved. Optimizations were coded to improve visualization, reduce the need for visual rendering, and decrease script execution time as well as the needed resources. To test the hypothesis, various optimization methods and algorithms were implemented on the initial visualization script and were tested. The main goal of this implementation was to assess how optimi

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Gubanov, Oleg, and Luca Cortelezzi. "On the cost efficiency of mixing optimization." Journal of Fluid Mechanics 692 (December 16, 2011): 112–36. http://dx.doi.org/10.1017/jfm.2011.498.

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AbstractIn this study we discuss the cost efficiency of the optimization of a new prototypical mixing flow, the Fourier sine flow, an extension of the sine flow. The Fourier sine flow stirs a mixture on a two-dimensional torus by blinking, at prescribed switching times, two orthogonal velocity fields with profiles represented by a Fourier sine series. We derive a family of mixers of increasing complexity by truncating the series to one, two, three and four modes. We consider the optimization of the velocity profiles and the optimization of the stirring protocol. We implement the former by comp

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Teng Fei, Teng Fei. "Research on Improved Ant Colony Optimization Based on Adaptive Chemical Reaction Optimization." 電腦學刊 32, no. 4 (2021): 166–78. http://dx.doi.org/10.53106/199115992021083204013.

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Cui-Cui Cai, Cui-Cui Cai, Mao-Sheng Fu Cui-Cui Cai, Xian-Meng Meng Mao-Sheng Fu, Qi-Jian Wang Xian-Meng Meng, and Yue-Qin Wang Qi-Jian Wang. "Modified Harris Hawks Optimization Algorithm with Multi-strategy for Global Optimization Problem." 電腦學刊 34, no. 6 (2023): 091–105. http://dx.doi.org/10.53106/199115992023123406007.

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<p>As a novel metaheuristic algorithm, the Harris Hawks Optimization (HHO) algorithm has excellent search capability. Similar to other metaheuristic algorithms, the HHO algorithm has low convergence accuracy and easily traps in local optimal when dealing with complex optimization problems. A modified Harris Hawks optimization (MHHO) algorithm with multiple strategies is presented to overcome this defect. First, chaotic mapping is used for population initialization to select an appropriate initiation position. Then, a novel nonlinear escape energy update strategy is presented to control t

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Şenol, Niyazi, Hasan U. Akay, and Şahin Yiğit. "A Gradient Enhanced Efficient Global Optimization-Driven Aerodynamic Shape Optimization Framework." Aerospace 12, no. 7 (2025): 644. https://doi.org/10.3390/aerospace12070644.

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The aerodynamic optimization of airfoil shapes remains a critical research area for enhancing aircraft performance under various flight conditions. In this study, the RAE 2822 airfoil was selected as a benchmark case to investigate and compare the effectiveness of surrogate-based methods under an Efficient Global Optimization (EGO) framework and an adjoint-based approach in both single-point and multi-point optimization settings. Prior to optimization, the computational fluid dynamics (CFD) model was validated against experimental data to ensure accuracy. For the surrogate-based methods, Krigi

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Nowak, M. "Improved aeroelastic design through structural optimization." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 2 (2012): 237–40. http://dx.doi.org/10.2478/v10175-012-0031-8.

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Abstract. The paper presents the idea of coupled multiphysics computations. It shows the concept and presents some preliminary results of static coupling of structural and fluid flow codes as well as biomimetic structural optimization. The model for the biomimetic optimization procedure was the biological phenomenon of trabecular bone functional adaptation. Thus, the presented structural bio-inspired optimization system is based on the principle of constant strain energy density on the surface of the structure. When the aeroelastic reactions are considered, such approach allows fulfilling the

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Rizky Amalia and Febriyanti Panjaitan. "Mask Detection Using Convolutional Neural Network Algorithm." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 4 (2022): 639–47. http://dx.doi.org/10.29207/resti.v6i4.4276.

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The World Health Organizations and the Ministry of Health of the Republic of Indonesia have required the use of masks to suppress the spread of COVID-19. WHO provides guidance on how to use a good mask to cover the mouth and nose. This study aims to detect the correct use of masks using the Convolutional Neural Network. CNN is a popular Deep Learning algorithm for image data classification problems. The Mask Usage Detector is built with the help of a pre-trained MobileNetV2 model with an architecture that supports media that has minimum computations. This study will also compare the performanc

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Kota, László, and Károly Jármai. "Improving optimization using adaptive algorithms." Pollack Periodica 16, no. 1 (2021): 14–18. http://dx.doi.org/10.1556/606.2020.00180.

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AbstractIn the research projects and industrial projects severe optimization problems can be met, where the number of variables is high, there are a lot of constraints, and they are highly nonlinear and mostly discrete issues, where the running time can be calculated sometimes in weeks with the usual optimization methods on an average computer. In most cases in the logistics industry, the most robust constraint is the time. The optimizations are running on a typical office configuration, and the company accepts the suboptimal solution what the optimization method gives within the appropriate t

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