Jo Devriendt ¹²³ Stephan Gocht ¹² Emir Demirović ⁴ Jakob Nordström ²¹ Peter J Stuckey ⁵
¹ Lund University, Sweden
² University of Copenhagen, Denmark
³ KU Leuven, Belgium
⁴ TU Delft, The Netherlands
⁵ Monash University, Australia
jodevriendt.com
slides.com/jod/coreguidedpb-full
Objective
(to minimize)
Solutions
Solutions
Objective
(to minimize)
Solutions
Objective
(to minimize)
Solutions
Objective
(to minimize)
Solutions
Objective
(to minimize)
Solutions
Objective
(to minimize)
Basically, we are doing 0-1 integer linear programming in this talk
Solver abstraction:
Solve under assumptions
Extract core
Reformulate problem
Increase lower bound
Solve under assumptions
Extract core
Reformulate problem
Increase lower bound
Advantage of cutting planes vs clausal
Lower bounds:
Lower bounds:
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
Solutions
Objective
(to minimize)
Related ideas in [ADMR15]
[PB16]
[PB16]
[PB16]
[PB16]
Our contribution
Cutting-planes reasoning advantages
Conclusion