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SUMMARY:Dr. Ambros Gleixner (Zuse Institute Berlin): Towards Verifiabl
 e Mixed-Integer Optimization
UID:70446d98-07fe-4423-9671-4c813b48b7bf
DESCRIPTION:ABSTRACT: Software for mixed-integer linear programming ca
 n return incorrect results for a number of reasons\, one being the use
  of inexact floating-point arithmetic. While standard floating-point s
 olvers yield satisfactory results for a vast majority of applications\
 , there are cases where provably correct answers are desirable. In thi
 s talk we will start with a short overview of algorithms for arithmeti
 cally exact mixed-integer linear programming. However\, even solvers t
 hat employ exact arithmetic may suffer from programming or algorithmic
  errors\, motivating the desire for a way to produce independently ver
 ifiable certificates of optimization results. Due to the complex natur
 e of state-of-the-art solution algorithms\, the ideal form of such a c
 ertificate is not entirely clear. We propose such a certificate format
 \, illustrating its capabilities and structure through examples. The c
 ertificate format is designed for easy verification and is composed of
  a list of statements that can be sequentially verified using a limite
 d number of simple yet powerful inference rules. Finally\, we present 
 a supplementary verification tool for compressing and checking these c
 ertificates independently of how they were created. We report computat
 ional results on a selection of mixed-integer linear programming insta
 nces from the literature. To this end\, we have extended the exact rat
 ional version of the solver SCIP to produce such certificates.
DTSTART:20161222T150000Z
DTEND:20161222T160000Z
LOCATION:H13
DTSTAMP:20260723T232119Z
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