Simulation based optimization of stochastic systems with integer design variables by sequential multipoint linear approximation

Abspoel, S.J.; Etman, L.F.P.; Vervoort, J.; Rooij, R. A. Van; Schoofs, A.J.G.; Rooda, J.E.

doi:10.1007/s001580100130

Cited by 16 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For optimization purposes, a nature-inspired particle swarm algorithm was used due to the high complexity and nonlinearity of the problem [57]. This procedure is characterized by a direct calculation method, which in contrast to approximation or deterministic methods such as response surface algorithms [58,59] requires numerous design calculations and thus, is more expensive. On the other hand, the optimization results are definite solutions of the respective problem and are not based on mathematical approximations.…”

Section: Discussionmentioning

confidence: 99%

Prediction of fracture healing under axial loading, shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli

Steiner

Claes

Ignatius

et al. 2013

J. R. Soc. Interface.

View full text Add to dashboard Cite

Numerical models of secondary fracture healing are based on mechanoregulatory algorithms that use distortional strain alone or in combination with either dilatational strain or fluid velocity as determining stimuli for tissue differentiation and development. Comparison of these algorithms has previously suggested that healing processes under torsional rotational loading can only be properly simulated by considering fluid velocity and deviatoric strain as the regulatory stimuli. We hypothesize that sufficient calibration on uncertain input parameters will enhance our existing model, which uses distortional and dilatational strains as determining stimuli, to properly simulate fracture healing under various loading conditions including also torsional rotation. Therefore, we minimized the difference between numerically simulated and experimentally measured courses of interfragmentary movements of two axial compressive cases and two shear load cases (torsional and translational) by varying several input parameter values within their predefined bounds. The calibrated model was then qualitatively evaluated on the ability to predict physiological changes of spatial and temporal tissue distributions, based on respective in vivo data. Finally, we corroborated the model on five additional axial compressive and one asymmetrical bending load case. We conclude that our model, using distortional and dilatational strains as determining stimuli, is able to simulate fracture-healing processes not only under axial compression and torsional rotation but also under translational shear and asymmetrical bending loading conditions.

show abstract

Section: Discussionmentioning

confidence: 99%

Prediction of fracture healing under axial loading, shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli

Steiner

Claes

Ignatius

et al. 2013

J. R. Soc. Interface.

View full text Add to dashboard Cite

show abstract

“…Abspoel et al (2001) have proposed a sequential approximate approach to solve SO with integer design variables. Sequential improvement can be appropriately used in different practical engineering design problems, (e.g.…”

Section: Sequential Improvementmentioning

confidence: 99%

Recent developments in metamodel based robust black-box simulation optimization: An overview

Parnianifard¹,

Azfanizam²,

Ariffin³

et al. 2019

10.5267/j.dsl

View full text Add to dashboard Cite

In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model's output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state-of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed.

show abstract

“…The literature in stochastic-constrained, discrete-valued simulation optimization is not vast, but it has received some attention in the last years: Abspoel et al (2001), Cezik and L'Ecuyer (2008), Atlason et al (2008), Davis and Ierapetritou (2009), Andradóttir and Kim (2010) and Kleijnen et al (2010).…”

Section: Vieira Junior Kienitz and Belderrainmentioning

confidence: 99%

Discrete-valued, stochastic-constrained simulation optimization with COMPASS

Vieira¹,

Kienitz²,

Belderrain³

2011

Proceedings of the 2011 Winter Simulation Conference (WSC)

View full text Add to dashboard Cite

We propose an improvement in the random search algorithm called COMPASS to allow it to deal with a single stochastic constraint.Our algorithm builds on two ideas: (a) a novel simulation allocation rule and (b) the proof that this new simulation allocation rule does not affect the asymptotic local convergence of the COMPASS algorithm.It is shown that the stochastic-constrained COMPASS has a competitive performance in relation to other well known algorithms found in the literature for discrete-valued, stochastic-constrained simulation problems.

show abstract

Simulation based optimization of stochastic systems with integer design variables by sequential multipoint linear approximation

Cited by 16 publications

References 15 publications

Prediction of fracture healing under axial loading, shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli

Prediction of fracture healing under axial loading, shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli

Recent developments in metamodel based robust black-box simulation optimization: An overview

Discrete-valued, stochastic-constrained simulation optimization with COMPASS

Contact Info

Product

Resources

About