Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 18th International C Peter J. Stuckey Conference p

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Towards a Compact SAT-Based Encoding of Itemset Mining Tasks,own declarative AI models, the problem is encoded as a constraints network or a propositional formula, whose associated models correspond to the patterns of interest. In this new declarative framework, new user-specified constraints can be easily integrated, while in traditional data mining, such ad

褪色

,A Pipe Routing Hybrid Approach Based on A-Star Search and Linear Programming, is to connect an input configuration to an output configuration by using a pipe composed of a succession of straight sections and bends. The pipe is routed within a 3D continuous space divided into non-regular convex cells in order to take obstacles into account. Our objective is to consider severa

原谅

使乳化

,Two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors,s on a limited number of processors. This decision problem is denoted by . in standard notations. The first technique is an extension of the Garey and Johnson algorithm that integrates precedence relations in energetic reasoning. The second one is an extension of the Leung, Palem and Pnueli algorith

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发电机

Hdl348

Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem, problems with implicit soft and hard constraints. In this paper, we consider a setup where one has offline access to symbolic, incomplete, problem knowledge, which cannot however be employed at search time. We show how such knowledge can be generally treated as a propagator, we devise an approach t

尽责

Learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems,thin a short time while minimizing costs. In this work, we consider the short-horizon planning of a problem variant where every order has to be delivered with the goal to minimize delivery tardiness, travel times, and labor costs of the drivers involved. Stochastic information as spatial and tempora

malapropism

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