An Update on the Comparison of MIP, CP and Hybrid Approaches for Mixed Resource Allocation and Scheduling

• Published in: Integration of Constraint Programming, Artificial Intelligence, and Operations Research Vol. 10848; pp. 403 - 411
• Main Author: Laborie, Philippe
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Constraint programming; CP Optimizer; Resource allocation; Scheduling
• ISBN: 9783319930305; 3319930303
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-93031-2_29

We consider a well known resource allocation and scheduling problem for which different approaches like mixed-integer programming (MIP), constraint programming (CP), constraint integer programming (CIP), logic-based Benders decompositions (LBBD) and SAT-modulo theories (SMT) have been proposed and experimentally compared in the last decade. Thanks to the recent improvements in CP Optimizer, a commercial CP solver for solving generic scheduling problems, we show that a standalone tiny CP model can out-perform all previous approaches and close all the 335 instances of the benchmark. The article explains which components of the automatic search of CP Optimizer are responsible for this success. We finally propose an extension of the original benchmark with larger and more challenging instances.