1118 eng reportzib TU Berlin 0 2010-03-15 2010-03-15 -- We propose a hybrid approach for solving the resource-constrained project scheduling problem which is an extremely hard to solve combinatorial optimization problem of practical relevance. Jobs have to be scheduled on (renewable) resources subject to precedence constraints such that the resource capacities are never exceeded and the latest completion time of all jobs is minimized. The problem has challenged researchers from different communities, such as integer programming (IP), constraint programming (CP), and satisfiability testing (SAT). Still, there are instances with 60 jobs which have not been solved for many years. The currently best known approach, lazyFD, is a hybrid between CP and SAT techniques. In this paper we propose an even stronger hybridization by integrating all the three areas, IP, CP, and SAT, into a single branch-and-bound scheme. We show that lower bounds from the linear relaxation of the IP formulation and conflict analysis are key ingredients for pruning the search tree. First computational experiments show very promising results. For five instances of the well-known PSPLIB we report an improvement of lower bounds. Our implementation is generic, thus it can be potentially applied to similar problems as well. 10-03 1438-0064 1226 urn:nbn:de:0297-zib-11180 App. in: CPAIOR 2010, Proceedings, Andrea Lodi et al. (eds.) Springer 2010, LNCS 6140, pp. 313-317 Timo Berthold unknown unknown Stefan Heinz Marco Lübbecke Rolf Möhring Jens Schulz 10-03 eng uncontrolled constraint integer programming eng uncontrolled cumulative constraint eng uncontrolled scheduling eng uncontrolled conflict analysis eng uncontrolled resource-constrained project Scheduling Mathematik Mathematical programming methods [See also 90Cxx] Integer programming Mathematical Optimization Berthold, Timo Heinz, Stefan Applied Optimization https://opus4.kobv.de/opus4-zib/files/1118/ZR_10_03.pdf https://opus4.kobv.de/opus4-zib/files/1118/ZR_10_03.ps