Special Issue of the EURO Journal on Computational Optimization:
Constraint Programming Approaches to Combinatorial Optimization
Submission Deadline: August 15, 2017
Combinatorial optimization is at the heart of many real-world
applications, while at the same time it is a vibrant and intellectually
challenging field of research. Some well-known application areas of
combinatorial optimization are vehicle routing, employee scheduling,
strategic planning, (financial) asset optimization, production
scheduling, timetabling, to name just a few. In this world with
ever-more available digital information, the developments in the field
of combinatorial optimization are increasingly more important to our
society.
The different contexts in which combinatorial problems arise have led to
a variety of solution techniques. For example, in Operations Research
(OR), the traditional application areas include logistics, supply chain
management, and resource allocation problems, while the solution
methodology is most often based on integer linear programming, or more
generally mathematical programming. On the other hand, the field of
Artificial Intelligence (AI) which has historically studied applications
such as motion planning, pattern recognition, and learning, is evolving
rapidly in the field of Machine Learning (ML). Most solution methods in
AI for combinatorial optimization utilize specialized search algorithms
and constraint reasoning techniques.
Based on a systematic search procedure and constraint propagation,
Constraint Programming (CP) has been the main paradigm for the
integration of techniques from OR and AI in the last decade. It has
fostered the development of new methodologies such as logic-based
Benders decomposition and CP-based column generation while providing a
framework for state-of-art algorithms for solving both challenging new
applications, for example determining the optimal power flow in electric
grids, and fundamental combinatorial optimization problems such as
max-clique or graph coloring.
We invite papers that combine ideas from algorithmic combinatorics,
mathematical programming, and artificial intelligence in the context of
constraint programming for solving combinatorial optimization problems.
Papers, in the EJCO format, should be submitted online
at https://www.editorialmanager.com/ejco/
Please select "S.I. : Constraint Programming Approaches to Combinatorial
Optimization 2017" when prompted.
Guest Editors:
Willem-Jan van Hoeve (vanhoeve@andrew.cmu.edu)
Louis-Martin Rousseau (Louis-Martin.Rousseau@cirrelt.ca)
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