The 2017 COIN-OR Cup is awarded to John Chinneck, Mubashsharul
Shafique, and Laurence Smith for their work on the CCGO Global
In a series of papers, this team developed an improved multi-start
method that can be used to find solutions for nonconvex NLPs. The
methodology is based on an approach called constraint consensus
concentration that attempts to identify disjoint parts of the feasible
region, and then launches a nonlinear solver for each of the disjoint
regions. CCGO relies on a mixture of novel theoretical developments,
heuristics, and algorithm engineering to create a software that
effectively and reliably finds solutions to difficult nonconvex
problems, comparing favorably to existing solvers. The implementation
of CCGO relies on COIN-OR software.
One of the main goals of the COIN-OR Cup is to promote effective use
of COIN-OR software that the community may not know about. The series
of papers nominated by John, Mubashsharul and Laurence is a perfect
example of that, and the prize committee is glad to announce them as
this year’s Cup winners.
Committee members: Andy Conn, Giacomo Nannicini, Thomas Wortmann.