About this Research Topic
The topics of the OPTARCH2019 Research Topic include, but are not limited to the following areas:
Shape and topology optimization: topological derivatives, level set methods, isogeometry-based shape optimization, topometry and topography optimization, sensitivity analysis, etc.
Linear, nonlinear, stochastic, parametric, discrete and dynamic programming – modelling.
Evolutionary algorithms, swarm optimization, scatter search, etc.
Parallel and distributed computing in optimization – Cloud computing, GPGPU computing environment.
Theory of metaheuristics, landscape analysis, convergence, large neighborhoods, etc.
Multiple criteria decision making and optimization.
Local search, tabu search, simulated annealing, VNS, ILS, etc.
Hybrid methods with metaheuristics, machine learning, game theory, mathematical programming, constraint programming, co-evolutionary, etc.
Energy (energy harvesting, storage, delivery, efficiency, etc.), environment and climate.
Artificial intelligence, surrogates-metamodels, fuzzy systems.
Structural optimization: composite materials, transient loads and crash, fatigue and fracture, etc.
Lifecycle design optimization and structural health monitoring.
Multidisciplinary and multiphysics design optimization.
Emergent nature inspired algorithms: quantum computing, artificial immune systems, DNA computing, etc.
Design under uncertainty: robust design optimization, reliability based design optimization, theoretical foundations and framework.
Optimization in emerging areas like micro- and nano-mechanics, multiscale, additive manufacturing.
Generative and parametic design.
Keywords: design optimization, architectural design, optimization, modelling, structural health monitoring, lifecycle design
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