Iterative repair for scheduling and rescheduling

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior

Solving the Resource Constrained Project Scheduling Problem with Generalized Precedences by Lazy Clause Generation

The technical report presents a generic exact solution approach for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedences (Rcpsp/max). The approach uses lazy clause generation, i.e., a hybrid of finite domain and Boolean satisfiability solving, in order to apply nogood learning and conflict-driven search on the solution generation. Our experiments show the benefit of lazy clause generation for finding an optimal solutions and proving its optimality in comparison to other state-of-the-art exact and non-exact methods. The method is highly robust: it matched or bettered the best known results on all of the 2340 instances we examined except 3, according to the currently available data on the PSPLib. Of the 631 open instances in this set it closed 573 and improved the bounds of 51 of the remaining 58 instances.Comment: 37 pages, 3 figures, 16 table

Constraint-based scheduling with total completion time criterion: models and applications

Abstract: Constraint programming (CP) offers flexible and effective tools for modeling combinatorial optimization problems. At the same time, scheduling with sum type optimization criteria, such as total completion time is challenging for CP. In this paper we show how extending a standard CP solver by a global constraint on total completion time can boost the performance of CP on various, seemingly very different optimization problems, including job shop scheduling, scheduling with tool changes, or even container loading. Copyright c○2007 IFAC Keywords: Constraint-based scheduling, global constraint, total completion time, applications 1

Rehearsal Scheduling Problem

Scheduling is a common task that plays a crucial role in many industries such as manufacturing or servicing. In a competitive environment, effective scheduling is one of the key factors to reduce cost and increase productivity. Therefore, scheduling problems have been studied by many researchers over the past thirty years. Rehearsal scheduling problem (RSP) is similar to the popular resource-constrained project scheduling problem (RCPSP); however, it does not have activity precedence constraints and the resources’ availabilities are not fixed during processing time. RSP can be used to schedule rehearsal in theatre industry or to schedule group scheduling when each member has different sets of available time. In this report, three different approaches are proposed to solve RSP including Constraint Programming, Integer Programming, and Schedule Generation Schemes

Beyond C<i>max</i>: an optimization-oriented framework for constraint-based scheduling

This paper presents a framework taking advantage of both the flexibility of constraint programming and the efficiency of operations research algorithms for solving scheduling problems under various objectives and constraints. Built upon a constraint programming engine, the framework allows the use of scheduling global constraints, and it offers, in addition, a modular and simplified way to perform optimality reasoning based on well-known scheduling relaxations. We present a first instantiation on the single machine problem with release dates and lateness minimization. Beyond the simplicity of use, the ptimizationoriented framework appears to be, from the experiments, effective for dealing with such a pure problem even without any ad-hoc heuristics

Beyond C<i>max</i>: an optimization-oriented framework for constraint-based scheduling

This paper presents a framework taking advantage of both the flexibility of constraint programming and the efficiency of operations research algorithms for solving scheduling problems under various objectives and constraints. Built upon a constraint programming engine, the framework allows the use of scheduling global constraints, and it offers, in addition, a modular and simplified way to perform optimality reasoning based on well-known scheduling relaxations. We present a first instantiation on the single machine problem with release dates and lateness minimization. Beyond the simplicity of use, the ptimizationoriented framework appears to be, from the experiments, effective for dealing with such a pure problem even without any ad-hoc heuristics