Author name cluster

Andreas Schutt

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers

1 author row

AAAI Conference 2020 Conference Paper

Modelling and Solving Online Optimisation Problems

Alexander Ek
Maria Garcia de la Banda
Andreas Schutt
Peter J. Stuckey
Guido Tack

Many optimisation problems are of an online—also called dynamic—nature, where new information is expected to arrive and the problem must be resolved in an ongoing fashion to (a) improve or revise previous decisions and (b) take new ones. Typically, building an online decision-making system requires substantial ad-hoc coding to ensure the ofﬂine version of the optimisation problem is continually adjusted and resolved. This paper deﬁnes a general framework for automatically solving online optimisation problems. This is achieved by extending a model of the ofﬂine optimisation problem, from which an online version is automatically constructed, thus requiring no further modelling effort. In doing so, it formalises many of the aspects that arise in online optimisation problems. The same framework can be applied for automatically creating sliding-window solving approaches for problems that have a large time horizon. Experiments show we can automatically create efﬁcient online and sliding-window solutions to optimisation problems.

PDF Details

JAIR Journal 2018 Journal Article

Optimal Torpedo Scheduling

Adrian Goldwaser
Andreas Schutt

We consider the torpedo scheduling problem in steel production, which is concerned with the transport of hot metal from a blast furnace to an oxygen converter. A schedule must satisfy, amongst other considerations, resource capacity constraints along the path and the locations traversed as well as the sulfur level of the hot metal. The goal is first to minimize the number of torpedo cars used during the planning horizon and second to minimize the time spent desulfurizing the hot metal. We propose an exact solution method based on Logic based Benders Decomposition using Mixed-Integer and Constraint Programming, which optimally solves and proves, for the first time, the optimality of all instances from the ACP Challenge 2016 within 10 minutes. In addition, we adapted our method to handle large-scale instances and instances with a more general rail network. This adaptation optimally solved all challenge instances within one minute and was able to solve instances of up to 100,000 hot metal pickups.

PDF Details DOI

IJCAI Conference 2013 Conference Paper

On the Complexity of Global Scheduling Constraints under Structural Restrictions

Geoffrey Chu
Serge Gaspers
Nina Narodytska
Andreas Schutt
Toby Walsh

This paper investigates the manpower allocation problem with time windows and job-teaming constraints (MAPTWTC), a practical scheduling and routing problem that tries to synchronize workers’ schedules to complete all tasks. We first provide an integer programming model for the problem and discuss its properties. Next, we show that tree data structure can be used to represent the MAPTWTC solutions, and its optimal solution can be obtained from one of trees by solving a minimum cost flow model for each worker type. Consequently, we develop for the problem a novel tabu search algorithm employing search operators based on the tree data structure. Finally, we prove the effectiveness of the tabu search algorithm by computational experiments on two sets of instances.

PDF Details DOI

IJCAI Conference 2013 Conference Paper

On the Complexity of Global Scheduling Constraints under Structural Restrictions

Geoffrey Chu
Serge Gaspers
Nina Narodytska
Andreas Schutt
Toby Walsh

We investigate the computational complexity of two global constraints, CUMULATIVE and INTERDISTANCE. These are key constraints in modeling and solving scheduling problems. Enforcing domain consistency on both is NP-hard. However, restricted versions of these constraints are often sufficient in practice. Some examples include scheduling problems with a large number of similar tasks, or tasks sparsely distributed over time. Another example is runway sequencing problems in air-traffic control, where landing periods have a regular pattern. Such cases can be characterized in terms of structural restrictions on the constraints. We identify a number of such structural restrictions and investigate how they impact the computational complexity of propagating these global constraints. In particular, we prove that such restrictions often make propagation tractable.

PDF Details DOI