Algorithmic Performance Guarantees: Foundations and Applications (APEG)
Project Summary
Optimization problems are ubiquitous in computer science. Almost every problem involves the optimization of some objective function. However a major part of these problems cannot be solved to optimality. Consequently, algorithms that achieve provably good performance guarantees are of immense importance. Considerable progress has already been made, but great challenges remain: Some fundamental problems are not well understood. Moreover, for important problems arising in new applications, no solutions are known at all.The goal of APEG is to significantly advance the state-of-the-art in the field of algorithmic performance guarantees. Specifically, the project has two missions: First, it will develop new algorithmic techniques in the areas of online algorithms, approximation algorithms and algorithmic game theory. Second, it will apply these techniques to solve fundamental problems that are central to these algorithmic disciplines. APEG will attack long-standing open problems. Furthermore, it will formulate and investigate new algorithmic problems that arise in modern applications. The research agenda encompasses a broad spectrum of classical and timely topics including (a) resource allocation in computer systems, (b) data structuring, (c) graph problems, with relations to Internet advertising, (d) complex networks and (e) massively parallel systems. In addition to basic optimization objectives, the project will also study the new performance metric of energy minimization in computer systems.
Affiliated Researchers
- Susanne Albers
- Waldo Gálvez (Postdoc at Universidad de O'Higgins, Chile), as of October 2021
- Maximilian Janke
- Arindam Khan (Professor at IIS Bengaluru, as of January 2019)
- Dennis Kraft (PhD completed in December 2018)
- Leon Ladewig (PhD completed in June 2021)
- Luisa Peter
- Jens Quedenfeld
- Sebstian Schubert
- Alexander Eckl
Publications
- S. Albers, J. Quedenfeld. Algorithms for right-sizing heterogeneous data centers.
In Proc. 33rd Symposium on Parallelism in Algorithms and Architectures (SPAA21),
48-58, 2021.
- S. Albers, S. Schubert.
Optimal algorithms for online b-matching with variable vertex capacities. In Proc. 24rd International Conference on Approximation
Algorithms for Combinatorial Optimization Problems (APPROX21), LIPIcs 207, 2:1-2:18, 2021.
- W. Gálvez, F. Grandoni, A. Khan, D. Ramírez-Romero, A. Wiese.
Improved approximation algorithms for 2-dimensional knapsack: Packing into multiple L-Shapes, spirals, and more. In Proc.
37th International Symposium on Computational Geometry (SoCG21), LIPIcs 189, 39:1-39:17, 2021.
- S. Albers, M. Janke. Online makespan minimization with budgeted uncertainty.
In Proc. 17th International Symposium on Algorithms and Data Structures (WADS21), Springer LNCS 12808, 43-56, 2021.
- S. Albers, J. Quedenfeld. Algorithms for energy conservation in heterogeneous data centers.
In Proc. 12th International Conference on Algorithms and Complexity (CIAC21), Springer LNCS 12701,
75-89, 2021.
- W. Gálvez, F. Grandoni, A. Jabal Ameli, K. Khodamoradi.
Approximation algorithms for demand strip packing. In Proc. 24rd International Conference on Approximation
Algorithms for Combinatorial Optimization Problems (APPROX21), LIPIcs 207, 20:1-20:25, 2021.
- S. Albers, A. Eckl. Scheduling with testing on multiple identical parallel machines.
In Proc. 17th International Symposium on Algorithms and Data Structures (WADS21), Springer LNCS 12808,
29-42, 2021.
- S. Albers, M. Janke. Scheduling in the secretary model.
In Proc. 41st Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS21), LIPIcs, 2021.
- S. Albers, W. Gálvez, M. Janke. Machine covering in the random-order model.
In Proc. 32nd International Symposium on Algorithms and Computation (ISAAC21), LIPIcs, 2021.
- S. Albers, D. Kraft.
On the value of penalties in time-inconsistent planning. ACM Trans. Economics and Comput., 9(3): 17:1-17:18, 2021.
- S. Albers, M. Janke.
Scheduling in the random-order model. Algorithmica, 83(9): 2803-2832, 2021.
- S. Albers, A. Khan, L. Ladewig.
Best Fit bin packing with random order revisited. Algorithmica, 83(9): 2833-2858, 2021.
- S. Albers, A. Khan, L. Ladewig.
Improved online algorithms for knapsack and GAP in the random order model. Algorithmica, 83(6): 1750-1785, 2021.
- S. Albers, L. Ladewig.
New results for the k-secretary problem. Theor. Comput. Sci., 863: 102-119, 2021.
- S. Albers, S. Schraink.
Tight bounds for online coloring of basic graph classes. Algorithmica, 83(1): 337–360, 2021.
- S. Albers, M. Janke.
Scheduling in the random-order model. In Proc. 47th International Colloquium on Automata, Languages, and Programming,
(ICALP20), LIPIcs 168, 68:1-68:18, 2020.
- S. Albers, M. Janke.
New bounds for randomized list update in the paid exchange model. In Proc. 37th International Symposium on Theoretical Aspects of Computer Science,
(STACS20), LIPIcs 154, 12:1-12:17, 2020.
- S. Albers, A. Khan, L. Ladewig.
Best Fit bin packing with random order revisited. In Proc. 45th International Symposium on Mathematical Foundations of Computer Science
(MFCS20), LIPIcs 170, 7:1-7:15, 2020.
- S. Albers, A. Eckl.
Explorable uncertainty in scheduling with non-uniform testing times. In Proc. 18th Workshop on Approximation and Online Algorithms,
(WAOA20), Springer LNCS 12806, 127-142, 2020.
- W. Gálvez, F. Grandoni, A. Jabal Ameli, K. Jansen, A. Khan, M. Rau.
A tight (3/2+ε) approximation for skewed strip packing. In Proc. 23rd International Conference on Approximation
Algorithms for Combinatorial Optimization Problems (APPROX20), LIPIcs 176, 44:1-44:18, 2020.
- S. Albers, A. Khan, L. Ladewig.
Improved online algorithms for knapsack and GAP in the random order model. In Proc. 22nd International Conference on Approximation
Algorithms for Combinatorial Optimization Problems (APPROX19), LIPIcs 145, 22:1-22:23, 2019.
- S. Albers, L. Ladewig.
New results for the k-secretary problem. In Proc. 30th International Symposium on Algorithms and Computation
(ISAAC19), LIPIcs 149, 18:1-18:19, 2019.
- S. Albers.
On energy conservation in data centers. ACM Trans. Parallel Comput., 6(3): 13:1-13:26, 2019.
- S. Albers, D. Kraft. Motivating time-inconsistent agents:
A computational approach. Theory of Computing Systems, 63(3):466–487, 2019.
- S. Albers, A. Passen.
New online algorithms for story scheduling in web advertising. Algorithmica, 81(1):1-25, 2019.
- J.R. Correa, P. Dütting, F.A. Fischer, K. Schewior.
Prophet inequalities for i.i.d. random variables from an unknown distribution. In Proc. 20th ACM Conference on Economics and Computation (EC19),
3-17, 2019.
- S. Albers, D. Frascaria.
Quantifying competitiveness in paging with locality of reference. Algorithmica, 80(12):3563-3596, 2018.
- S. Albers, J. Quedenfeld. Optimal algorithms for right-sizing data centers.
In Proc. 30th Symposium on Parallelism in Algorithms and Architectures (SPAA18),
363-372, 2018.
- S. Albers, E. Bampis, D. Letsios, G. Lucarelli, R. Stotz.
Scheduling on power-heterogeneous processors. Information and Computation, 257:22-33, 2017.
- S. Albers, D. Kraft. The price of uncertainty in
present-biased planning. In Proc. 13th International Conference on Web and Internet Economics (WINE17),
Springer LNCS, 2017.
- S. Albers, M. Hellwig.
On the value of job migration in online makespan minimization. Algorithmica, 79(2):598-623, 2017.
- S. Albers, S. Schraink. Tight bounds for online coloring of basic
graph classes. In Proc. 25th Annual European Symposium on Algorithms (ESA17), 7:1-7:14, 2017.
- S. Albers, D. Kraft. On the value of penalties in time-inconsistent planning.
In Proc. 44rd International Colloquium on Automata, Languages, and Programming (ICALP17), 10:1-10:12, 2017.
- Y. Giannakopoulos, E. Koutsoupias, P. Lazos.
Online market intermediation. In Proc. 44rd International Colloquium on
Automata, Languages, and Programming (ICALP17), 47:1-47:14, 2017.
- S. Albers.
On energy conservation in data centers. In Proc. 29th ACM Symposium on Parallelism in Algorithms and Architectures
(SPAA17), 35-44, 2017.
- W. Gálvez, F. Grandoni, S. Heydrich, S. Ingala, A. Khan, A. Wiese.
Approximating geometric knapsack via L-packings. In Proc. 58th IEEE Annual Symposium on Foundations of Computer Science
(FOCS17), 260-271, 2017.
- S. Albers, M. Hellwig.
Online makespan minimization with parallel schedules. Algorithmica, 78(2):492-520, 2017.
- S. Albers, D. Kraft. Motivating time-inconsistent agents:
A computational approach. In Proc. 12th International Conference on Web and Internet Economics (WINE16),
Springer LNCS 10123, 309-323, 2016.
- S. Albers, E. Bampis, D. Letsios, G. Lucarelli, R. Stotz.
Scheduling on power-heterogeneous processors. In Proc. 12th Latin American Symposium on Theoretical Informatics (LATIN16),
Springer LNCS 9644, 41-54, 2016.
- S. Albers, S. Lauer.
On list update with locality of reference. J. Comput. Syst. Sci., 82(5):627-653, 2016.