Multi-objective Adaptive Guided Differential Evolution for Passively Controlled Structures Equipped with a Tunned Mass Damper

Springer tracts in nature-inspired computing, Journal Year: 2024, Volume and Issue: unknown, P. 45 - 66

Published: Jan. 1, 2024

Language: Английский

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Multi-modal Routing in Urban Transportation Network Using Multi-objective Quantum Particle Swarm Optimization

Springer tracts in nature-inspired computing, Journal Year: 2024, Volume and Issue: unknown, P. 133 - 154

Published: Jan. 1, 2024

Language: Английский

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Multi-objective Lichtenberg Algorithm for the Optimum Design of Truss Structures

Springer tracts in nature-inspired computing, Journal Year: 2024, Volume and Issue: unknown, P. 95 - 114

Published: Jan. 1, 2024

Language: Английский

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Multi-objective Routing Optimization of the Traveling Salesman Problem Using Feasibility-Enhanced Particle Swarm Optimization Algorithm

Published: Jan. 1, 2025

Language: Английский

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Positron-Enabled Atomic Orbital Search Algorithm for Improved Reliability-Based Design Optimization

Published: Jan. 1, 2023

Reliability-based design optimization (RBDO) is an essential process in designing reliable engineering systems. However, most metaheuristic algorithms used to solve RBDO problems suffer from premature convergence and low search efficiency. To address this, enhanced algorithm called the positron-enabled atomic orbital (PAOS) proposed. Assuming of positronium annihilation subsequent emission double gamma-ray, energy needed excite electrons generated. As a result, residual ion can be influenced by electron positron contained within positronium, leading production desired target atom. This chapter provides performance analysis PAOS on reliability-based two real-world problems: tuned mass dampers soil-nail wall system. The results demonstrate that significantly terms both speed accuracy. Furthermore, this investigates impact various parameters discusses potential applications problems. algorithm's flexibility, efficiency, ability explore space effectively make it promising tool for solving

Language: Английский

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Overcoming Constraints: The Critical Role of Penalty Functions as Constraint-Handling Methods in Structural Optimization

Published: Jan. 1, 2023

Optimization problems are common in many fields, including engineering, finance, and logistics. These often involve complex objective functions multiple constraints that must be satisfied simultaneously. To solve such problems, various optimization algorithms have been developed employ different constraint-handling methods. This chapter provides an overview of these methods compares their effectiveness solving problems. The most commonly used methods, penalty functions, discussed evaluated. optimum design framed structures is a problem requires balancing variety competing objectives, as minimizing weight while maintaining structural integrity. Several applied to structures, performance compared terms solution quality, computational efficiency, robustness. results show the choice method can significantly affect outcome may more effective depending on specific involved.

Language: Английский

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Synergistic Collaboration of Motion-Based Metaheuristics for the Strength Prediction of Cement-Based Mortar Materials Using TSK Model

Published: Jan. 1, 2023

Considering mortar material's extensive use in construction over the last few decades, a robust and reliable method is required to estimate its strength based on mix parameters. The reason behind this complex nonlinear connection between compressive of constituent components. This research investigates utilization artificial intelligence methods predict cement-based materials, both with without metakaolin. A surrogate model, specifically Takagi-Sugeno-Kang (TSK) was created mortars existing experimental data found literature. findings demonstrate that TSK model can effectively reliably mortars. To prevent from overfitting during validation process new data, it optimized using mean square error (MSE) criterion. end, collaborative motion-based algorithm incorporating charged system search (CSS) colliding bodies optimization (CBO) employed. Consequently, developed presented as most suitable predictive technique for addressing issue prediction

Language: Английский

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Optimized fuzzy logic and sliding mode control for stability and disturbance rejection in rotary inverted pendulum

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Language: Английский

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Boosting the Efficiency of Metaheuristics Through Opposition-Based Learning in Optimum Locating of Control Systems in Tall Buildings

Published: Jan. 1, 2023

Opposition-based learning (OBL) is an effective approach to improve the performance of metaheuristic optimization algorithms, which are commonly used for solving complex engineering problems. This chapter provides a comprehensive review literature on use opposition strategies in discussing benefits and limitations this approach. An overview strategy concept, its various implementations, impact algorithms presented. Furthermore, case studies application problems provided, including optimum locating control systems tall building. A shear frame with magnetorheological (MR) fluid damper considered as study. The results demonstrate that incorporation significantly enhances quality speed process. aims provide clear understanding applications, ultimate goal facilitating adoption real-world

Language: Английский

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Incorporating Nelder-Mead Simplex as an Accelerating Operator to Improve the Performance of Metaheuristics in Nonlinear System Identification

Published: Jan. 1, 2023

This chapter explores the use of Nelder-Mead simplex (NMS) as an accelerating operator to improve performance metaheuristic algorithms, which are commonly used for solving complex optimization problems. NMS is a search method that forms points, iteratively transforming it find optimal solution. The incorporation in algorithms can significantly enhance convergence speed and solution quality. solutions each iteration modified by several operations reflection, contraction, expansion algorithm. A case study nonlinear system identification structural dynamics presented. problem defined estimate parameters Bouc-Wen model magnetorheological damper (MRD). results demonstrate accelerates improves proposed methods offer promising enhancing

Language: Английский

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