Evolutionary algorithms for constrained engineering problems
Computers and Industrial Engineering
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Multi-physics optimization of three-dimensional microvascular polymeric components
Journal of Computational Physics
Hi-index | 31.45 |
This paper describes a framework for the design of microvascular polymeric components for active cooling applications. The design of the embedded networks involves complex and competing objectives that are associated with various physical processes. The optimization tool includes a PDE solver based on advanced finite element techniques coupled to a multi-objective constrained genetic algorithm. The resulting Pareto-optimal fronts are investigated in the optimization of these materials for void volume fraction, flow efficiency, maximum temperature, and surface convection objective functions.