Robust dual-response optimization

Yanıkoğlu, İhsan; Hertog, Dick den; Kleijnen, J.P.C.

doi:10.1080/0740817x.2015.1067737

Cited by 29 publications

(13 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is reasonable, as the economic data are all influenced from the same market developments [63]. Then, the uncertainty set can be assumed as ellipsoidal (for other Φ-divergence uncertainty sets see [62,64]). The constraint can be written as:…”

Section: Expected Return Uncertaintymentioning

confidence: 99%

Coarse Woody Debris Management with Ambiguous Chance Constrained Robust Optimization

Härtl

Knoke

2019

Forests

View full text Add to dashboard Cite

Coarse woody debris (deadwood) serves as a dwelling space for many rare species, and is therefore a most important factor to ensure diversity in forest ecosystems. However, wood from forest ecosystems is also needed for construction and heating. Therefore, a forest enterprise has to simultaneously incorporate the provision of suitable habitats, as well as the production of wood into their long-term management plans. If the owner wants to fulfil such multiple objectives in an effective way, the providing of ecosystem services can be included in economic planning. Applying computer aided robust optimization techniques, we optimized the provision of deadwood for two exemplary enterprises in East Bavaria, Germany. The results show that high amounts of deadwood provision can cause severe opportunity costs for the forest owner. These costs highly depend on the tree species, the sorting strategy and the time horizon, in which the deadwood objective is reached. Low deadwood targets up to 5 m 3 h a − 1 can be provided most cost-effectively with crown material, while higher targets (20 m 3 h a − 1 and more) are better achieved with heavy timber grades or the provision of total trees. The novelty of our research is the inclusion of deadwood targets in a risk-considering optimization tool on enterprise level. Instead of calculating the economic loss of commercially not-used timber assortments we show a way of deriving the impact of such decisions at stand level on the economic performance of the whole forest enterprise. We were able to derive optimized opportunity costs. These costs can be used as guidelines for necessary incentives to encourage forest owners to incorporate the provision of deadwood into their management.

show abstract

Section: Expected Return Uncertaintymentioning

confidence: 99%

Coarse Woody Debris Management with Ambiguous Chance Constrained Robust Optimization

Härtl

Knoke

2019

Forests

View full text Add to dashboard Cite

show abstract

“…Notably, there are different optimization approaches available on dual response methodology where some of them are referenced in (Ardakani & Noorossana, 2008;Beyer & Sendhoff, 2007;Nha et al, 2013;Yanikoglu et al, 2016), so here just for instance some common methods of them are mentioned in Table 3.…”

Section: Dual Response Surface Methodsmentioning

confidence: 99%

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

Parnianifard¹,

Azfanizam²,

Ariffin³

et al. 2018

10.5267/j.ijiec

View full text Add to dashboard Cite

Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems under real operational conditions such as dynamic objectives, multiresponses, various probabilistic distribution, discrete and continuous data, physical constraints to design parameters, performance cost, computational complexity and multi-process environment. The main goal of this paper is to give a general overview on topics with brief systematic review and concise discussions about the recent development on comprehensive robust design optimization methods under hybrid aforesaid circumstances. Both optimization methods of mathematical programming based on Taguchi approach and robust optimization based on scenario sets are briefly described. Metamodels hybrid robust design is discussed as an appropriate methodology to decrease computational complexity in problems under uncertainty. In this context, the authors' policy is to choose important topics for giving a systematic picture to those who wish to be more familiar with recent studies about robust design optimization hybrid metamodels, also by attending real circumstances in practice. In particular, production and project management are considered as two important methodologies that could be improved by applications of advanced robust design combining with metamodel methods.

show abstract

“…As a consequence, it searches for an optimal set of input variables to optimize the response by using a set of designed experiments. In the past few years, several robust DRSO techniques have been developed [12,13]. Yanikoglu et al (2016) introduced Taguchi's Robust Parameter Design approach into DRSO to develop a method that uses only experimental data, and it can yield a solution that is robust against ambiguity in the probability of inputs [12].…”

Section: Introductionmentioning

confidence: 99%

Developing a Statistical Model to Improve Drinking Water Quality for Water Distribution System by Minimizing Heavy Metal Releases

Peng

Mayorga

2018

Water

View full text Add to dashboard Cite

This paper proposes a novel statistical approach for blending source waters in a public water distribution system to improve water quality (WQ) by minimizing the release of heavy metals (HMR). Normally, introducing a new source changes the original balanced environment and causes adverse effects on the WQ in a water distribution system. One harmful consequence of blending source water is the release of heavy metals, including lead, copper and iron. Most HMR studies focus on the forecasting of unfavorable effects using precise and complicated nonlinear equations. This paper uses a statistical multiple objectives optimization, namely Multiple Source Waters Blending Optimization (MSWBO), to find optimal blending ratios of source waters for minimizing three HMRs in a water supply system. In this paper, three response surface equations are applied to describe the reaction kinetics of HMR, and three dual response surface equations are used to track the standard deviations of the three response surface equations. A weighted sum method is performed for the multi-objective optimization problem to minimize three HMRs simultaneously. Finally, the experimental data of a pilot distribution system is used in the proposed statistical approach to demonstrate the model's applicability, computational efficiency, and robustness.Keywords: water quality (WQ); blending; release of heavy metals (HMR); dual response surface optimization (DRSO); multiple source waters blending optimization (MSWBO)

show abstract

Robust dual-response optimization

Cited by 29 publications

References 36 publications

Coarse Woody Debris Management with Ambiguous Chance Constrained Robust Optimization

Coarse Woody Debris Management with Ambiguous Chance Constrained Robust Optimization

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

Developing a Statistical Model to Improve Drinking Water Quality for Water Distribution System by Minimizing Heavy Metal Releases

Contact Info

Product

Resources

About