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Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 19th International C Pierre Schaus Conference proc

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樓主: 惡夢(mèng)
61#
發(fā)表于 2025-4-1 04:37:19 | 只看該作者
,Efficient Operations Between MDDs and?Constraints,se operations involve an MDD that represents the result of past operations and a new constraint. This approach is efficient, but it is very difficult to implement with some constraints such as . or cardinality constraints because it is often impossible to represent them by an MDD because of their si
62#
發(fā)表于 2025-4-1 08:44:48 | 只看該作者
,Deep Policy Dynamic Programming for?Vehicle Routing Problems, to learn approximate solution heuristics for such problems. In contrast, classical dynamic programming (DP) algorithms guarantee optimal solutions, but scale badly with the problem size. We propose . (DPDP), which aims to combine the strengths of learned neural heuristics with those of DP algorithm
63#
發(fā)表于 2025-4-1 11:20:41 | 只看該作者
64#
發(fā)表于 2025-4-1 14:31:30 | 只看該作者
,A FastMap-Based Algorithm for?Block Modeling, existing block modeling algorithms work directly on the given graphs, making them computationally expensive and less effective on large complex graphs. In this paper, we propose a FastMap-based algorithm for block modeling on single-view undirected graphs. FastMap embeds a given undirected graph in
65#
發(fā)表于 2025-4-1 20:02:57 | 只看該作者
,Packing by?Scheduling: Using Constraint Programming to?Solve a?Complex 2D Cutting Stock Problem, from rectangular stocks using guillotine cuts with the objective to minimize waste. Motivated by our industrial partner and different from problems in the literature, the 2SCSP-FF allows both the length of individual items and the total area of orders to vary within customer-specified intervals. We
66#
發(fā)表于 2025-4-2 00:16:43 | 只看該作者
,Dealing with?the?Product Constraint,lems, this constraint appears more and more frequently in practice. The variables are most often probability variables that represent the probability that an event will occur and the minimum bound is the minimum probability that must be satisfied. This is often done to guarantee a certain level of s
67#
發(fā)表于 2025-4-2 05:44:10 | 只看該作者
Multiple-choice Knapsack Constraint in Graphical Models,thms. Most methods for computing lower bounds in Branch-and-Bound minimization compute feasible dual solutions of a specific linear relaxation. These methods are more effective than solving the linear relaxation exactly, with better worst-case time complexity and better performance in practice. Howe
68#
發(fā)表于 2025-4-2 10:20:26 | 只看該作者
d . species for effective and efficient use in chickpea breeding programmes. Limiting factors to crop production, possible solutions and ways to overcome them, importance of wild relatives and barriers to alien gene introgression and strategies to overcome them and traits for base broadening have be
69#
發(fā)表于 2025-4-2 11:45:41 | 只看該作者
Eddie Armstrong,Michele Garraffa,Barry O’Sullivan,Helmut Simonismulated by providing open-ended mathematical tasks. Not only that, it is also argued that openness of problems is more conducive to students’ mathematical creativity compared to using closed tasks. In this chapter we examine this assumption and make a case for ‘constraints-based’ task design. In thi
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