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Documents authored by Hong, Liu

Found 2 Possible Name Variants:

Hong, Liu

Document
DOI: 10.4230/DagSemProc.09181.3
09181 Working Group on Hybridization between R&S, DoE and Optimization

Authors: Chun-Hung Chen, Liu Hong, Paul B. Kantor, David P. Morton, Juta Pichitlamken, and Matthias Seeger

Published in: Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009)

Abstract
This is the report of the working group on the relation between, or hybrid combination of design experiment optimization and R&S. The rapporteur, Paul Kantor, learned a great deal at the conference which he summarized by sharing the cartoon shown here. ("A student asking the teacher'... may i be excused, my is full" (from a 1986 cartoon by Gary Larson) - omitted here for copyright reasons).
Cite as

Chun-Hung Chen, Liu Hong, Paul B. Kantor, David P. Morton, Juta Pichitlamken, and Matthias Seeger. 09181 Working Group on Hybridization between R&S, DoE and Optimization. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{chen_et_al:DagSemProc.09181.3,
  author =	{Chen, Chun-Hung and Hong, Liu and Kantor, Paul B. and Morton, David P. and Pichitlamken, Juta and Seeger, Matthias},
  title =	{{09181 Working Group on Hybridization between R\&S, DoE and Optimization}},
  booktitle =	{Sampling-based Optimization in the Presence of Uncertainty},
  pages =	{1--14},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9181},
  editor =	{J\"{u}rgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.3},
  URN =		{urn:nbn:de:0030-drops-21172},
  doi =		{10.4230/DagSemProc.09181.3},
  annote =	{Keywords: }
}

Liu, Fu-Hong

Document
DOI: 10.4230/LIPIcs.MFCS.2024.69
Scheduling with Locality by Routing

Authors: Alison Hsiang-Hsuan Liu and Fu-Hong Liu

Published in: LIPIcs, Volume 306, 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)

Abstract
This work examines a strongly NP-hard routing problem on trees, in which multiple servers need to serve a given set of requests (on vertices), where the routes of the servers start from a common source and end at their respective terminals. Each server can travel free of cost on its source-to-terminal path but has to pay for travel on other edges. The objective is to minimize the maximum cost over all servers. As the servers may pay different costs for traveling through a common edge, balancing the loads of the servers can be difficult. We propose a polynomial-time 4-approximation algorithm that applies the parametric pruning framework but consists of two phases. The first phase of the algorithm partitions the requests into packets, and the second phase of the algorithm assigns the packets to the servers. Unlike the standard parametric pruning techniques, the challenge of our algorithm design and analysis is to harmoniously relate the quality of the partition in the first phase, the balances of the servers' loads in the second phase, and the hypothetical optimal values of the framework. For the problem in general graphs, we show that there is no algorithm better than 2-approximate unless P = NP. The problem is a generalization of unrelated machine scheduling and other classic scheduling problems. It also models scheduling problems where the job processing times depend on the machine serving the job and the other jobs served by that machine. This modeling provides a framework that physicalizes scheduling problems through the graph’s point of view.
Cite as

Alison Hsiang-Hsuan Liu and Fu-Hong Liu. Scheduling with Locality by Routing. In 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 306, pp. 69:1-69:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{liu_et_al:LIPIcs.MFCS.2024.69,
  author =	{Liu, Alison Hsiang-Hsuan and Liu, Fu-Hong},
  title =	{{Scheduling with Locality by Routing}},
  booktitle =	{49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)},
  pages =	{69:1--69:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-335-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{306},
  editor =	{Kr\'{a}lovi\v{c}, Rastislav and Ku\v{c}era, Anton{\'\i}n},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2024.69},
  URN =		{urn:nbn:de:0030-drops-206250},
  doi =		{10.4230/LIPIcs.MFCS.2024.69},
  annote =	{Keywords: Makespan minimization, Approximation algorithms, Routing problems, Parametric pruning framework}
}
Document
DOI: 10.4230/LIPIcs.ISAAC.2016.53
Optimal Nonpreemptive Scheduling in a Smart Grid Model

Authors: Fu-Hong Liu, Hsiang-Hsuan Liu, and Prudence W. H. Wong

Published in: LIPIcs, Volume 64, 27th International Symposium on Algorithms and Computation (ISAAC 2016)

Abstract
We study a scheduling problem arising in demand response management in smart grid. Consumers send in power requests with a flexible feasible time interval during which their requests can be served. The grid controller, upon receiving power requests, schedules each request within the specified interval. The electricity cost is measured by a convex function of the load in each timeslot. The objective is to schedule all requests with the minimum total electricity cost. Previous work has studied cases where jobs have unit power requirement and unit duration. We extend the study to arbitrary power requirement and duration, which has been shown to be NP-hard. We give the first online algorithm for the general problem, and prove that the worst case competitive ratio is asymptotically optimal. We also prove that the problem is fixed parameter tractable. Due to space limit, the missing proofs are presented in the full paper.
Cite as

Fu-Hong Liu, Hsiang-Hsuan Liu, and Prudence W. H. Wong. Optimal Nonpreemptive Scheduling in a Smart Grid Model. In 27th International Symposium on Algorithms and Computation (ISAAC 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 64, pp. 53:1-53:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{liu_et_al:LIPIcs.ISAAC.2016.53,
  author =	{Liu, Fu-Hong and Liu, Hsiang-Hsuan and Wong, Prudence W. H.},
  title =	{{Optimal Nonpreemptive Scheduling in a Smart Grid Model}},
  booktitle =	{27th International Symposium on Algorithms and Computation (ISAAC 2016)},
  pages =	{53:1--53:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-026-2},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{64},
  editor =	{Hong, Seok-Hee},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2016.53},
  URN =		{urn:nbn:de:0030-drops-68252},
  doi =		{10.4230/LIPIcs.ISAAC.2016.53},
  annote =	{Keywords: Scheduling, Smart Grid, Convex function cost, Fixed parameter tractable, Online algorithms, Non-preemptive}
}
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