A5050214535- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Topology Optimization in Engineering
- Probabilistic and Robust Engineering Design
- Marine and Offshore Engineering Studies
- Evolutionary Algorithms and Applications
- Offshore Engineering and Technologies
- Aerospace Engineering and Control Systems
- Maritime Transport Emissions and Efficiency
- Wind Energy Research and Development
- Mechanical Engineering and Vibrations Research
- Heat Transfer and Optimization
- Advanced Aircraft Design and Technologies
- Vehicle Routing Optimization Methods
- Aeroelasticity and Vibration Control
- Advanced Wireless Communication Technologies
- Guidance and Control Systems
- Optimal Experimental Design Methods
- Composite Structure Analysis and Optimization
- Optimization and Mathematical Programming
- Neurological disorders and treatments
- Optimization and Packing Problems
- Ship Hydrodynamics and Maneuverability
- Full-Duplex Wireless Communications
- Religion and Sociopolitical Dynamics in Nigeria
University of Tasmania
2021-2025
Australian Maritime College
2021-2024
Manav Rachna International Institute of Research and Studies
2024
Rajalakshmi Engineering College
2022
Panjab University
2022
Gujarat Technological University
2018-2021
Indian Institute of Technology Kanpur
2015
Abstract This work proposed a new metaheuristic dubbed as Chaotic Lévy flight distribution (CLFD) algorithm, to address physical world engineering optimization problems that incorporate the chaotic maps in elementary (LFD). Hybridization aims increase LFD rate of convergence while also providing problem‐free approach. The methodology is investigated for five case studies constrained issues followed by shape structural design. outcomes from CFLD algorithm are further contrasted with its...
Green hydrogen is a key element that has the potential to play critical role in global pursuit of resilient and sustainable future. However, like other energy production methods, comes with challenges, including high costs safety concerns across its entire value chain. To overcome these, low-cost productions are required along promised market. Offshore renewables have an enormous facilitate green on large scale. Their plummeting cost, technological advances, rising cost carbon pave pathway...
Abstract In this article, a new prairie dog optimization algorithm (PDOA) is analyzed to realize the optimum economic design of three well-known heat exchangers. These exchangers found numerous applications in industries and are an imperative part entire thermal systems. Optimization these includes knowledge thermo-hydraulic designs, parameters critical constraints. Moreover, cost factor always challenging task optimize. Accordingly, total optimization, including initial maintenance, has...
Abstract In this present work, mechanical engineering optimization problems are solved by employing a novel optimizer (HFDO-DOBL) based on physics-based flow direction (FDO) and dynamic oppositional-based learning. Five real-world problems, viz. planetary gear train, hydrostatic thrust bearing, robot gripper, rolling multiple disc clutch brake, considered. The computational results obtained HFDO-DOBL compared with several newly proposed algorithms. statistical analysis demonstrates the...
Many-objective truss structure problems from small to large-scale with low high design variables are investigated in this study. Mass, compliance, first natural frequency, and buckling factor assigned as objective functions. Since there limited optimization methods that have been developed for solving many-objective issues, it is important assess modern algorithms performance on these issues develop more effective techniques the future. Therefore, study contributes by investigating...
In this study, a multi-objective version of the recently proposed cheetah optimizer called (MOCO) has been proposed. MOCO draws inspiration from targeted hunting strategy employed by cheetahs, which involves sequence actions: searching for prey, patiently waiting right moment to attack, swiftly launching and then retreating prey returning their habitat. is result modification enhancement its single-objective counterpart, utilizing Pareto dominance-based approach. This adaptation allows...
This paper proposes a new Multi-Objective Plasma Generation Optimization (MOPGO) algorithm, and its non-dominated sorting mechanism is investigated for numerous challenging real-world structural optimization design problems. The (PGO) algorithm recently reported physics-based inspired by the generation process of plasma in which electron movement energy level are based on excitation modes, de-excitation, ionization processes. As search progresses, better balance between exploration...
Abstract Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over classical optimization techniques. In present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on artificial hummingbird (AHA) simulated annealing problem is proposed to improve performance of AHA. To check HAHA-SA, it was applied solve three constrained design problems. For comparative...
Abstract Optimization of engineering discipline problems are quite a challenging task as they carry design parameters and various constraints. Metaheuristic algorithms can able to handle those complex realize the global optimum solution for problems. In this article, novel generalized normal distribution algorithm that is integrated with elite oppositional-based learning (HGNDO-EOBL) studied employed optimize eight benchmark functions. Moreover, statistical results obtained from HGNDO-EOBL...
This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted optimization for airfoil shape optimization.The problem is posed to maximize the lift and drag coefficient ratio subject geometry constraints.Computational Fluid Dynamic (CFD) XFoil tools are used high low-fidelity simulations of find real objective function value.A special sub-optimization proposed multiple points infill sampling exploration improve surrogate model constructed.To validate further assess...
Unlocking the potential of offshore renewables for green hydrogen (GH2) production can be a game-changer, empowering economies with their visionary clean energy policies, amplifying security, and promoting economic growth. However, novelty entails uncertainty risk, necessitating robust framework facility deployment infrastructure planning. To optimize GH2 placement, this work proposes novel GIS-based multi-criteria decision-making (MCDM) framework. Encompassing thirty-two...
The multiobjective (MO) optimizers show great promise in solving constrained engineering structural problems. This paper introduces a MO version of the Brown Bear Optimization (BBO) algorithm, inspired by foraging behavior brown bears. proposed Multiobjective (MOBBO) algorithm is applied to five optimization problems, including 10‐bar, 25‐bar, 60‐bar, 72‐bar, and 942‐bar trusses, aiming minimize both mass maximum nodal deflection simultaneously. Comparative evaluations against six benchmark...