Performance of the Gittins policy in the G/G/1 and G/G/k, with and without setup times

Hong, Yige; Scully, Ziv

doi:10.1016/j.peva.2023.102377

Cited by 3 publications

(2 citation statements)

References 53 publications

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“…The precipitates at "point 3" are mainly contains N, C, Nb, and Ti elements, and the results are M(C, N) type carbonitrides, which is consistent with the research results in literature. [27,28] The precipitation position of "point 5" is mainly distributed intermittently along, mainly containing C, Cr, and Mo elements. Compared with the carbon concentration in coarse block carbides, that in granular carbides on the grain boundaries is significantly reduced.…”

Section: Microstructuresmentioning

confidence: 99%

Study on the High Temperature Tensile Properties and Strengthening Mechanism of Nitrogen Containing Nickel‐Based Deposited Metals

Dai,

Su,

Wang

et al. 2024

Adv Eng Mater

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This article investigates the tensile properties and strengthening mechanism of nitrogen‐containing nickel‐based flux cored welding wire deposited metal from room temperature to 900 °C. The results showed that the high‐temperature strength of the deposited metal increased with the addition of Tungsten and Nitrogen. When the temperature reaches 700 °C, M23C6 carbides begin to decompose. The alloying elements dissolve back into the matrix, and the solid solution strengthening effect minimizes the plasticity of the alloy. More carbonitrides are precipitated within the crystal with temperature. During high‐temperature deformation, carbonitrides fractures at the interface with the substrate due to difficulty in coordinating deformation. Therefore, the crack source formed greatly reduces the strength of the material. In addition, the stacking faults present in the low‐temperature zone have a significant impact on the work hardening of materials. The main deformation mechanism is the unit dislocation a/2 < 110> cutting precipitation phase. It can be observed that the dislocation cutting precipitation mechanism system has transformed into a dislocation bypassing precipitation mechanism system at intermediate. Finally, the anomalous yield strength (YS) and intermediate temperature brittleness phenomenon are reasonably explained. The main deformation mechanism gradually transforms into dislocation slip and climbing with temperature.

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Section: Microstructuresmentioning

confidence: 99%

Study on the High Temperature Tensile Properties and Strengthening Mechanism of Nitrogen Containing Nickel‐Based Deposited Metals

Dai,

Su,

Wang

et al. 2024

Adv Eng Mater

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“…In this article, we applied the principle of orthogonal design to analyze the data space of precipitation start and finish times (P s and P f , respectively) collected from published literatures. [8,[18][19][20][21][22][23][24][25][26][27][28][29][30] The missing data are supplemented by making new steel grades and hot deformation experiments. Based on the orthogonally modified dataset, the ML was established in combination with theoretical modeling for SIP behavior of Nb micro-alloyed steels.…”

Section: Introductionmentioning

confidence: 99%

Physical Metallurgy Guided Machine Learning for Strain‐Induced Precipitation of Nb (C, N) Based on the Orthogonalized Small Data

Jiang

Cui

et al. 2023

steel research int.

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Strain‐induced precipitation (SIP) plays an important role in controlling the microstructure and properties of micro‐alloyed steels during hot rolling. However, due to lack of systematic experiments, the existing precipitation data are scarce and insufficient for accurate modeling of SIP behavior with good extrapolation. Herein, the data space of Niobium Carbonitride (Nb(C,N)) SIP kinetics is analyzed based on principle of orthogonal design, and the missing points in the orthogonal space are identified and supplemented in addition to the available data. The parameters in models for precipitation start and finish times are optimized by using the precipitation–time–temperature curves through genetic algorithm, and their relationships with compositions and processing conditions are established by support vector machine. Based on the orthogonally modified dataset, the machine learning (ML) models outperform the classical and ML models with the original data in terms of accuracy and are in good agreement with theoretical expectations. By using the new ML modeling, the evolution behavior of Nb (C, N) during hot deformation is predicted and verified with transmission electron microscope, and the influences of Nb content in steel, strain, strain rate, and the sensitivity of compositions and processing conditions on precipitation kinetics are quantitatively analyzed.

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Strongly Tail-Optimal Scheduling in the Light-Tailed M/G/1

Yu,

Scully

2024

Proc. ACM Meas. Anal. Comput. Syst.

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We study the problem of scheduling jobs in a queueing system, specifically an M/G/1 with light-tailed job sizes, to asymptotically optimize the response time tail. This means scheduling to make \mathbfP [T > t], the chance a job's response time exceeds t, decay as quickly as possible in the t \to \infty limit. For some time, the best known policy was First-Come First-Served (FCFS), which has an asymptotically exponential tail: \mathbfP [T > t] \sim C e^-γ t . FCFS achieves the optimal *decay rate* γ, but its *tail constant* C is suboptimal. Only recently have policies that improve upon FCFS's tail constant been discovered. But it is unknown what the optimal tail constant is, let alone what policy might achieve it. In this paper, we derive a closed-form expression for the optimal tail constant C, and we introduce *γ-Boost*, a new policy that achieves this optimal tail constant. Roughly speaking, γ-Boost operates similarly to FCFS, but it pretends that small jobs arrive earlier than their true arrival times. This significantly reduces the response time of small jobs without unduly delaying large jobs, improving upon FCFS's tail constant by up to 50% with only moderate job size variability, with even larger improvements for higher variability. While these results are for systems with full job size information, we also introduce and analyze a version of γ-Boost that works in settings with partial job size information, showing it too achieves significant gains over FCFS. Finally, we show via simulation that γ-Boost has excellent practical performance.

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Performance of the Gittins policy in the G/G/1 and G/G/k, with and without setup times

Cited by 3 publications

References 53 publications

Study on the High Temperature Tensile Properties and Strengthening Mechanism of Nitrogen Containing Nickel‐Based Deposited Metals

Study on the High Temperature Tensile Properties and Strengthening Mechanism of Nitrogen Containing Nickel‐Based Deposited Metals

Physical Metallurgy Guided Machine Learning for Strain‐Induced Precipitation of Nb (C, N) Based on the Orthogonalized Small Data

Strongly Tail-Optimal Scheduling in the Light-Tailed M/G/1

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