Multi-objective optimisation in scientific workflow

Nguyen, Hoang Anh; Iperen, Zane van; Raghunath, Sreekanth; Abramson, David; Kipouros, Timoleon; Somasekharan, Sandeep

doi:10.1016/j.procs.2017.05.213

Cited by 13 publications

(10 citation statements)

References 18 publications

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“…There are many optimization techniques proposed for improving the performance of scientific workflows [10], [11]. We have classified those into two groups: a) optimization methods and b) scheduling techniques.…”

Section: B Related Workmentioning

confidence: 99%

Adaptive Optimizations for Stream-based Workflows

Liang

Filguiera

Yan

2020

2020 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS)

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This work presents three new adaptive optimization techniques to maximize the performance of dispel4py workflows. dispel4py is a parallel Python-based stream-orientated dataflow framework that acts as a bridge to existing parallel programming frameworks like MPI or Python multiprocessing. When a user runs a dispel4py workflow, the original framework performs a fixed workload distribution among the processes available for the run. This allocation does not take into account workflows' features, which can cause scalability issues, specially for data-intensive scientific workflows. Therefore, our aim is to improve the performance of dispel4py workflows by testing different workload strategies that automatically adapt to workflows. For achieving this objective, we have implemented three new techniques, called Naive Assignment, Staging and Dynamic Scheduling. The evaluations show that our proposed techniques have significantly improved the performance of the original dispel4py framework.

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Section: B Related Workmentioning

confidence: 99%

Adaptive Optimizations for Stream-based Workflows

Liang

Filguiera

Yan

2020

2020 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS)

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“…6 and 7 were identified in the multi -objective study to maximize simultaneously. In multi-objective optimization, it is possible to have multiple peak points in contrast 17,18 . For this balance, weight factors are used for combining multiple functions into one single function 17 .…”

Section: Distillate M Distillate M Distillate M Residue 5amentioning

confidence: 99%

“…In multi-objective optimization, it is possible to have multiple peak points in contrast 17,18 . For this balance, weight factors are used for combining multiple functions into one single function 17 . In this study, our aim was to separate oleic acid from the mixture with the highest purity as possible.…”

Section: Distillate M Distillate M Distillate M Residue 5amentioning

confidence: 99%

Multi-objective Optimization of Molecular Distillation Conditions for Oleic Acid from a Rich-in-Fatty Acid Model Mixture

2018

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Oleic acid is a commercially valuable compound and has many positive health effects. Determining optimum conditions in a physical separation process is an industrially significant point due to environmental and health related concerns. Molecular distillation avoids the use of chemicals and adverse effects of high temperature application. The objective of this study was to determine the molecular distillation conditions for oleic acid to increase its purity and distillation yield in a model fatty acid mixture. For this purpose, a short-path evaporator column was used. Evaporation temperature ranged from 110 to 190℃, while absolute pressure was from 0.05 to 5 mmHg. Results showed that elevating temperature generally increased distillation yield until a maximum evaporation temperature. Vacuum application also affected the yield at a given temperature, and amount of distillate increased at higher vacuums except the case applied at 190℃. A multi-objective optimization procedure was then used for maximizing both yield and oleic acid amounts in distillate simultaneously, and an optimum point of 177.36℃ and 0.051 mmHg was determined for this purpose. Results also demonstrated that evaporation of oleic acid was also suppressed by a secondary dominant fatty acid of olive oil - palmitic acid, which tended to evaporate easier than oleic acid at lower evaporation temperatures, and increasing temperature achieved to transfer more oleic acid to distillate. At 110℃ and 0.05 mmHg, oleic and palmitic acid concentrations in distillate were 63.67% and 24.32%, respectively. Outcomes of this study are expected to be useful for industrial process conditions.

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“…Multi-objective optimization has been applied in engineering fields where optimal decisions must be made in the presence of two or more objectives, such as the power, which is the product of torque and velocity, and weight of a rotary machine. Multi-objective design optimization has been implemented in many engineering applications, such as airfoil shape optimization [9], engine design [10] and optimal controller design [11].…”

Section: Introductionmentioning

confidence: 99%

Study on the Design of an Underwater Chain Trencher via a Genetic Algorithm

Kim

Kwon

Hai

et al. 2019

JMSE

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In this study, a genetic algorithm (GA) with an analytic model is adopted to conduct multi-objective optimization for design of an underwater chain trencher. The optimization problem is defined as minimizing a product of the chain power and weight subject to the uniaxial compressive strength, coefficient of traction, bar length (L), nose radius (R) and ratio of the chipping depth over the spacing (l/S), of which the ranges are determined based on the specifications of commercial trenchers satisfying established performance requirements and previous parametric studies. It is found that an optimal design of the GA was obtained with L and l/S close to their low bound and R far from its low bound while that of a simple parametric analysis was acquired with the three parameters close to their low bounds. Moreover, in the most severe soft rock and traction conditions, the power and weight in the optimal design obtained by the GA are turn to be within the feasible ranges of targeted commercial trenchers.

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Multi-objective optimisation in scientific workflow

Cited by 13 publications

References 18 publications

Adaptive Optimizations for Stream-based Workflows

Adaptive Optimizations for Stream-based Workflows

Multi-objective Optimization of Molecular Distillation Conditions for Oleic Acid from a Rich-in-Fatty Acid Model Mixture

Study on the Design of an Underwater Chain Trencher via a Genetic Algorithm

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