CAST10 Archives

February 2022

CAST10@LISTSERV.UMD.EDU

Options: Use Monospaced Font
Show HTML Part by Default
Condense Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Content-Type:
multipart/alternative; boundary="_000_3791F3B6216C4D7AB1912B7663F5ED86univcotedazurfr_"
X-To:
Date:
Tue, 15 Feb 2022 11:03:54 +0000
Reply-To:
Marie Pelleau <[log in to unmask]>
Subject:
From:
Marie Pelleau <[log in to unmask]>
Message-ID:
MIME-Version:
1.0
Sender:
"Chemical Engineers in Computing and Systems Technology, AIChE" <[log in to unmask]>
Parts/Attachments:
text/plain (3448 bytes) , text/html (6 kB)
****************** Our apologies for multiple reception of this announcement *****************
****** This call can be seen online: https://sites.google.com/usc.edu/cpaior-2022/cfp ******

Call for extended abstracts

The 19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research will be held in Los Angeles, US, June 20th-June 23th, 2022.

The aim of the conference is to bring together interested researchers from Constraint Programming (CP), Artificial Intelligence (AI), and Operations Research (OR) to present new techniques or applications and to provide an opportunity for researchers in one area to learn about techniques in the others. A main objective of this conference series is also to give these researchers the opportunity to show how the integration of techniques from different fields can lead to interesting results on large and complex problems. Therefore, papers that actively combine, integrate, or contrast approaches from more than one of the areas are especially solicited. High quality papers from a single area are also welcome, if they are of interest to other communities involved. Application papers showcasing CP/AI/OR techniques on novel and challenging applications or experience reports on such applications are strongly encouraged.

The program committee invites submissions that include but are not limited to the following topics:
  -  Inference and relaxation methods: constraint propagation, cutting planes, global constraints, graph algorithms, dynamic programming, Lagrangian and convex relaxations, heuristic functions based on constraint relaxation.
  - Search methods: branch and bound, intelligent backtracking, incomplete search, randomized search, portfolios, column generation, Benders decompositions or any other decomposition methods, local search, meta-heuristics.
  - AI and Machine Learning techniques applied to solve optimization and Operations Research problems or CP/OR techniques to solve AI and machine learning problems.
  - Integration methods: solver communication, model transformations and solver selection, parallel and distributed solving, combining machine learning with combinatorial optimization.
  - Modeling methods: comparison of models, symmetry breaking, uncertainty, dominance relationships.
  - Innovative applications of CP/AI/OR techniques.
  - Implementation of CP/AI/OR techniques and optimization systems.


Extended abstracts should be 1 or 2 pages in length and may present preliminary work or work already published in other outlets. The extended abstracts are submitted for presentation only (if accepted), and will not be formally published in the LNCS conference volume. A collection of the accepted extended abstracts will be published on the conference website. A submission representing work submitted or published in another outlet should state that outlet. Extended abstracts will be reviewed to ensure appropriateness for the conference.

Submission Process

All extended abstracts are to be submitted electronically in PDF format by following the instructions at the URL https://easychair.org/conferences/?conf=cpaior2022

Submission schedule for extended abstracts:

Abstract: March 3, 2022 (AoE)

Notification: April 4th, 2022

Questions

For any queries on the submission process, please contact the Program Chair Pierre Schaus at: [log in to unmask]<mailto:[log in to unmask]>



ATOM RSS1 RSS2