TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Lübbecke, Marco A1 - Möhring, Rolf A1 - Schulz, Jens T1 - A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling N2 - 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. T3 - ZIB-Report - 10-03 KW - constraint integer programming KW - cumulative constraint KW - scheduling KW - conflict analysis KW - resource-constrained project Scheduling Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11180 SN - 1438-0064 ER - TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Schulz, Jens T1 - An approximative Criterion for the Potential of Energetic Reasoning N2 - Energetic reasoning is one of the most powerful propagation algorithms in cumulative scheduling. In practice, however, it is not commonly used because it has a high running time and its success highly depends on the tightness of the variable bounds. In order to speed up energetic reasoning, we provide an easy-to-check necessary condition for energetic reasoning to detect infeasibilities. We present an implementation of energetic reasoning that employs this condition and that can be parametrically adjusted to handle the trade-off between solving time and propagation overhead. Computational results on instances from the PSPLIB are provided. These results show that using this condition decreases the running time by more than a half, although more search nodes need to be explored. T3 - ZIB-Report - 11-12 KW - conflict analysis KW - constraint integer programming KW - cumulative constraint KW - resource-constrained project scheduling KW - energetic reasoning Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12655 ER - TY - GEN A1 - Heinz, Stefan A1 - Schulz, Jens T1 - Explanations for the Cumulative Constraint: an Experimental Study N2 - In cumulative scheduling, conflict analysis seems to be one of the key ingredients to solve such problems efficiently. Thereby, the computational complexity of explanation algorithms plays an important role. Even more when we are faced with a backtracking system where explanations need to be constructed on the fly. In this paper we present extensive computational results to analyze the impact of explanation algorithms for the cumulative constraint in a backward checking system. The considered explanation algorithms differ in their quality and computational complexity. We present results for the domain propagation algorithms time-tabling, edge-finding, and energetic reasoning. T3 - ZIB-Report - 11-13 KW - conflict analysis KW - constraint integer programming KW - cumulative constraint KW - resource-constrained project scheduling KW - propagation algorithms Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12668 ER - TY - GEN A1 - Heinz, Stefan A1 - Schulz, Jens A1 - Beck, J. Christopher T1 - Using dual presolving reductions to reformulate cumulative constraints N2 - Dual presolving reductions are a class of reformulation techniques that remove feasible or even optimal solutions while guaranteeing that at least one optimal solution remains, as long as the original problem was feasible. Presolving and dual reductions are important components of state-of-the-art mixed-integer linear programming solvers. In this paper, we introduce them both as unified, practical concepts in constraint programming solvers. Building on the existing idea of variable locks, we formally define and justify the use of dual information for cumulative constraints during a presolving phase of a solver. In particular, variable locks are used to decompose cumulative constraints, detect irrelevant variables, and infer variable assignments and domain reductions. Since the computational complexity of propagation algorithms typically depends on the number of variables and/or domain size, such dual reductions are a source of potential computational speed-up. Through experimental evidence on resource constrained project scheduling problems, we demonstrate that the conditions for dual reductions are present in well-known benchmark instances and that a substantial proportion of them can be solved to optimality in presolving -- without search. While we consider this result very promising, we do not observe significant change in overall run-time from the use of our novel dual reductions. T3 - ZIB-Report - 12-37 KW - dual reductions KW - cumulative constraints KW - presolving KW - variable locks Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-16321 SN - 1438-0064 ER - TY - CHAP A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Schulz, Jens T1 - An approximative Criterion for the Potential of Energetic Reasoning T2 - Theory and Practice of Algorithms in (Computer) Systems Y1 - 2011 VL - 6595 SP - 229 EP - 239 ER - TY - CHAP A1 - Heinz, Stefan A1 - Schulz, Jens T1 - Explanations for the Cumulative Constraint: An Experimental Study T2 - Experimental Algorithms Y1 - 2011 VL - 6630 SP - 400 EP - 409 ER - TY - CHAP A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Lübbecke, Marco A1 - Möhring, Rolf A1 - Schulz, Jens ED - Lodi, Andrea ED - Milano, Michela ED - Toth, Paolo T1 - A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling T2 - Proc. of CPAIOR 2010 Y1 - 2010 VL - 6140 SP - 313 EP - 317 PB - Springer ER - TY - GEN A1 - Schlechte, Thomas A1 - Blome, Christian A1 - Gerber, Stefan A1 - Hauser, Stefan A1 - Kasten, Jens A1 - Müller, Gilbert A1 - Schulz, Christof A1 - Thüring, Michel A1 - Weider, Steffen T1 - The Bouquet of Features in Rolling Stock Rotation Planning T2 - Conference Proceedings RailBelgrade 2023 N2 - Rolling stock is one of the major assets for a railway transportation company. Hence, their utilization should be as efficiently and effectively as possible. Railway undertakings are facing rolling stock scheduling challenges in different forms - from rather idealized weekly strategic problems to very concrete operational ones. Thus, a vast of optimization models with different features and objectives exist. Thorlacius et al. (2015) provides a comprehensive and valuable collection on technical requirements, models, and methods considered in the scientific literature. We contribute with an update including recent works. The main focus of the paper is to present a classification and elaboration of the major features which our solver R-OPT is able to handle. Moreover, the basic optimization model and algorithmic ingredients of R-OPT are discussed. Finally, we present computational results for a cargo application at SBB CARGO AG and other railway undertakings for passenger traffic in Europe to show the capabilities of R-OPT. Y1 - 2023 UR - https://easychair.org/publications/preprint/Nms6 ER -