Call for Papers

The International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2025), co-located with RANDOM 2025, will take place at UC Berkeley, Berkeley, California, USA, on August 11-13, 2025.

We invite submissions of papers presenting original research in all areas related to approximation algorithms for combinatorial optimization problems.

Submission Guidelines

Submissions, in PDF, should start with a title page containing the title of the paper, each author’s name, affiliation, and e-mail address, and a 1-2 paragraph abstract summarizing the paper’s contributions. The title page should be followed by a technical exposition on single-spaced, single-column pages, letter-size paper, using page numbers, at least 1-inch margins all around, and at least 11-point font. The first 10 pages, following the title page, should contain a clear presentation of the main technical and conceptual ideas underlying the results, including the motivation behind the paper and a clear comparison with related work (not including the references). The submission should be accessible to a wide variety of researchers in theoretical computer science and discrete mathematics. There is no page limit, but any material beyond the title page and the following 10 pages will be read at the sole discretion of the program committee.

Work that has been previously published in another conference proceedings or journal, or which will be published before the end of the conference, will not be considered for acceptance. Simultaneous submission of the same (or an overlapping) paper to RANDOM/APPROX and to another conference with published proceedings is not allowed.

You can find the official call for papers here.

Important Deadlines

1. Submissions: May 8, 2025, AoE Time Zone
2. Notifications: July 1, 2025
3. Camera ready: July 15, 2025

Scope

Papers are solicited in all research areas related to approximation, including but not limited to:

• approximation algorithms
• hardness of approximation
• small space, sub-linear time and streaming algorithms
• online algorithms
• approaches that go beyond worst-case analysis
• distributed and parallel approximation​
• embeddings and metric space methods
• mathematical programming methods
• spectral methods
• combinatorial optimization
• algorithmic game theory, mechanism design and economics
• computational geometric problems
• approximate learning

Program Committee

• Jose Correa, Universidad de Chile
• Yotam Dikstein, IAS
• Michael Dinitz, Johns Hopkins University
• Alina Ene (PC Chair), Boston University
• D Ellis Hershkowitz, Brown University
• Billy Jin, University of Chicago
• Nathan Klein, Boston University
• Jochen Koenemann, University of Waterloo
• Jason Li, CMU
• Quanquan Liu, Yale University
• Vasilis Livanos, Universidad de Chile
• Viswanath Nagarajan, University of Michigan
• Martin Naegele, ETH Zurich
• Liren Shan, TTI Chicago
• Zihan Tan, Rutgers University
• Vera Traub, ETH Zurich
• Laura Vargas Koch, RWTH Aachen University
• Samson Zhou, Texas A&M University