Abstract Additive manufacturing (AM) has an affinity with topology optimization to think of various designs complex structures. Hence, this paper aims optimize the design a lattice-structured heat sink, which can be manufactured by AM. The objectives are maximize thermal performance convective transfer in natural convection simulated computational fluid dynamics (CFD) and minimize material cost required for AM process at same time. lattice structure is represented as node/edge system via...

A sophisticated GA/PSO-hybrid algorithm for application to real-world optimization problems was proposed. The configurations of the two consisting methods, GA and PSO, were investigated enhance diversity former fast convergence latter simultaneously. new hybrid applied test function problems, results indicated that search ability improved by suitable tuning configurations. In addition, showed robust regardless selection initial population. also a diesel engine combustion chamber design...

Computationally expensive multiobjective optimization problems are difficult to solve using solely evolutionary algorithms (EAs) and require surrogate models, such as the Kriging model. To efficiently, we propose infill criteria for appropriately selecting multiple additional sample points updating These correspond expected improvement of penalty-based boundary intersection (PBI) inverted PBI. PBI-based measures increasingly applied EAs due their ability explore better nondominated solutions...

A new constraint-handling method based on Pareto-optimality and niching concepts for multi-objective multi-constraint evolutionary optimization is proposed. The proposed does not require any constants to be tuned constraint-handling. In addition, the present use weighted-sum of constraints thus tuning weight coefficients efficient even when all individuals in initial population are infeasible or amount violation each constraint significantly different. approach demonstrated remarkably more...

Summary A non‐gradient‐based approach for topology optimization using a genetic algorithm is proposed in this paper. The used paper assisted by the Kriging surrogate model to reduce computational cost required function evaluation. To validate method flow problems, research focuses on two single‐objective where objective functions are minimize pressure loss and maximize heat transfer of channels, one multi‐objective problem, which combines earlier problems. shape channels represented level...

This paper presents a comparison of the criteria for updating Kriging surrogate models in multi-objective optimization: expected improvement (EI), hypervolume (EHVI), estimation (EST), and those combination (EHVI + EST). EI has been conventionally used as criterion considering stochastic each objective function value individually, while EHVI recently proposed front nondominated solutions optimization. EST is estimated nonstochastically by model without its uncertainties. Numerical...

This paper presents a comparison of the criteria for updating Kriging surrogate models in surrogate-based non-constrained many-objective optimization: expected improvement (EI), hypervolume (EHVI), and estimate (EST). EI has been conventionally used as criterion considering stochastic each objective function value individually, while EHVI proposed front nondominated solutions multi-objective optimization. EST is estimated non-stochastically by model without its uncertainties. Numerical tests...

This paper proposes a novel approach for fluid topology optimization using genetic algorithm. In this study, the enhancement of mixing in passive micromixers is considered. The efficient achieved by grooves attached on bottom microchannel and optimal configuration investigated. are represented based graph theory. performance analyzed CFD solver exploration algorithm assisted Kriging model to reduce computational cost. characteristics convex concave compared. To balance global reasonable...

Surrogate models are invaluable tools that greatly assist the process of computationally expensive analyses and optimization. Engineering optimization reaps benefit from surrogate in order to perform could potentially be intractable pre-high-performance computing age. Moreover, provide a means allow engineering design exploration with high-fidelity computer simulations. Despite their wide use substantial research progresses, there still some key issues challenges need addressed by...

The technique of parallelization is a trend in the field Bayesian global optimization (BGO) and important for real-world applications because it can make full use CPUs speed up execution times. This paper proposes multi-point mechanism expected hypervolume improvement (EHVI) multi-objective BGO (MOBGO) by utilization truncated EHVI (TEHVI). basic idea to divide objective space into several sub-objective spaces then search optimal solutions each using TEHVI as infill criterion. We studied...

The composite kernel learning (CKL) method is introduced to efficiently construct kernels for Gaussian process (GP) surrogate models with applications in engineering design. mixture of functions cast as a weighted-sum model which the weights are treated extra hyperparameters yield higher optimum likelihood. CKL framework aims improve accuracy GP and relieves difficulty selection. In this paper, combination five studied, namely, Gaussian, Matérn-3/2, Matérn-5/2, exponential, cubic, each...

An aerodynamic design optimization problem of a three-dimensional flapping wing is explored with the multiobjective exploration framework coupled Navier – Stokes solver. The results show that there tradeoff among lift maximization, thrust and required power minimization. also strong vortex generated in both down stroke up motions for maximization while only motion maximization. This study reveals effects parameters on objectives, example, pitch offset has positive linear relationship to lift.

One of the difficulties in multi-disciplinary design optimization lies complicated interactions between large numbers objective functions, variables, and constraints. This difficulty often leads to an unsuitable formulation problems. Data mining is used address these challenges. provides insight into systems. The information obtained from data can be support (a) problems, (b) decision making, (c) steering. report presents a review recent developments applications techniques engineering...