Single-machine scheduling with tool changes: a constraint-based approach

The paper addresses the scheduling of a single machine with tool changes in order to minimize total completion time. A constraint-based model is proposed that makes use of global constraints and also incorporates various dominance rules. With these techniques, our constraint-based approach outperforms previous exact solution methods

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

A global constraint for total weighted completion time for cumulative resources

The criterion of total weighted completion time occurs as a sub-problem of combinatorial optimization problems in such diverse areas as scheduling, container loading and storage assignment in warehouses. These applications often necessitate considering a rich set of requirements and preferences, which makes constraint programming (CP) an effective modeling and solving approach. On the other hand, basic CP techniques can be inefficient in solving models that require inference over sum type expressions. In this paper, we address increasing the solution efficiency of constraint-based approaches to cumulative resource scheduling with the above criterion. Extending previous results for unary capacity resources, we define the COMPLETIONm global constraint for propagating the total weighted completion time of activities that require the same cumulative resource. We present empirical results in two different problem domains: scheduling a single cumulative resource, and container loading with constraints on the location of the center of gravity. In both domains, the proposed constraint propagation algorithm out-performs existing propagation techniques

Incorporation of Functionalized Polyhedral Oligomeric Silsesquioxane Nanomaterials as Reinforcing Agents for Impact Ice Mitigating Coatings

In-flight, aircraft are exposed to a wide range of environments. One commonly exposed environment are clouds containing super-cooled water droplets. These water drop- lets exist in a metastable state below the freezing point of water, in the range of 0 to -20C. As the vehicle impacts the droplets, latent heat is released and within milliseconds the droplets convert to ice. This process is referred to as impact icing or in-flight icing.1 Impact icing is a major concern for aircraft since it can lead to degraded aerodynamic performance and, if left un- treated, can lead to loss of the vehicle. Active approaches (i.e., pneumatic boots, heated air ducts) typically utilized in mitigating in-flight ice accretion significantly increases vehicle weight and cannot be applied to all aircraft.1-3 A passive approach based on coatings is desired, but durability issues are a concern, especially on the wing leading edge.3 Nanomaterials have been shown to afford significant improvement in coating and composite physical properties at low loading levels.4 In this study, Polyhedral Oligomeric Silsesquioxane (POSS) nanomaterials have been shown to increase coating durability. Also, with wide variety of functionalities present on the arm structure, POSS nanomaterials have been shown to readily alter coating surface chemistry to mitigate impact ice adhesion from -16 to -8C in a simulated in-flight icing environment