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

态度暖昧

Ikram Nekkache,Said Jabbour,Lakhdar Sais,Nadjet Kamel

食道

Marvin Stanczak,Cédric Pralet,Vincent Vidal,Vincent Baudoui

PLIC

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painkillers

A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Schedulo devise a destructive lower bounding method. We perform an extensive computational study across thousands of instances based on the PSPlib to quantify the impact of project size, potential learning occurrences, and learning effects on the optimal project duration. In addition, we compare formulatio

吸引人的花招

Strengthening of Feasibility Cuts in Logic-Based Benders Decomposition, obtain irreducible cuts. In particular, the use of the depth-first binary search cut-strengthening algorithm gives a good performance. Another observation is that when the subproblem can be separated into small independent problems, the impact of cut strengthening is dominated by that of the separa

Brain-Waves

Deadpan

Partitioning Students into Cohorts During COVID-19,ses. We solve this problem by modeling it as an integer linear program, and apply our model to generate the Master Timetable for a Canadian all-boys high school, successfully enrolling students in 87% of their desired courses, including 100% of their required courses. We conclude the paper by explai

DALLY

Heavy-Tails and Randomized Restarting Beam Search in Goal-Oriented Neural Sequence Decoding,we propose a randomized restarting variant of beam search. We conduct extensive empirical evaluation, comparing different randomization techniques and restart strategies, and show that the randomized restarting variant solves some of the hardest instances faster and outperforms the baseline.

evaculate

,Combining Constraint Programming and Temporal Decomposition Approaches - Scheduling of an Industriaall instances of the scheduling problem monolithically. To deal with large instances a decomposition algorithm is developed. The overall set of batches is divided into subsets which are scheduled iteratively. The algorithm is designed in a moving horizon fashion, in order to counteract the disadvant