Strong polynomiality of resource constraint propagation

نویسندگان

  • Luc Mercier
  • Pascal Van Hentenryck
چکیده

Constraint-based schedulers have been widely successful to tackle complex, disjunctive and cumulative, scheduling applications by combining tree search and constraint propagation. The constraint-propagation step is a fixpoint algorithm that applies pruning operators to tighten the release and due dates of activities using precedence or resource constraints. A variety of pruning operators for resource constraints have been proposed: they are based on edge finding or energetic reasoning and handle a single resource. Complexity results in this area are only available for a single application of these pruning operators, which is problematic for at least two reasons. On the one hand, the operators are not idempotent so a single application is rarely sufficient. On the other hand, the operators are not used in isolation but interact with each other. Existing results thus provide a very partial picture of the complexity of propagating resource constraints in constraint-based scheduling. This paper aims at addressing these limitations. It studies, for the first time, the complexity of applying pruning operators for resource constraints to a fixpoint. In particular, it shows that (1) the fixpoint of the edge finder for both release and due dates can be reached in strongly polynomial time for disjunctive scheduling; (2) the fixpoint can be reached in strongly polynomial time for updating the release dates or the due dates but not both for the cumulative scheduling; (3) the fixpoint of “reasonable” energetic operators cannot be reached in strongly polynomial time, even for disjunctive scheduling and even when only the release dates or the due dates are considered.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Explaining Time-Table-Edge-Finding Propagation for the Cumulative Resource Constraint

Cumulative resource constraints can model scarce resources in scheduling problems or a dimension in packing and cutting problems. In order to efficiently solve such problems with a constraint programming solver, it is important to have strong and fast propagators for cumulative resource constraints. Time-table-edge-finding propagators are a recent development in cumulative propagators, that com...

متن کامل

Incremental Propagation of Time Windows on Disjunctive Resources

Constraint-based techniques are frequently used in solving real-life scheduling problems thanks to natural modeling capabilities and strong constraint propagation techniques encoded within global constraints. In this paper we present new incremental propagation rules for shrinking time windows of activities allocated to a disjunctive resource. These rules use information about precedence constr...

متن کامل

A Time and Resource Problem for Planning Architectures

This paper concerns the problem of resource reasoning in planning. It defines formally a constraint satisfaction problem, the Time and Resource Problem (T RP), in which resource reasoning is seen as integrated with temporal reasoning. Two propagation techniques are introduced that reason about resource constraints in the T RP framework. The Profile Propagation technique, similar to time-tabling...

متن کامل

Checking the Consistency of Combined Qualitative Constraint Networks

We study the problem of consistency checking for constraint networks over combined qualitative formalisms. We propose a framework which encompasses loose integrations and a form of spatio-temporal reasoning. In particular, we identify sufficient conditions ensuring the polynomiality of consistency checking, and we use them to find tractable subclasses.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Discrete Optimization

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2007