Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 17th International C Emmanuel Hebrard,Nysret Musli

Ischemia

Bilevel Optimization for On-Demand Multimodal Transit Systemsential riders adopt the new ODMTS or stay with their personal vehicles. It is motivated by the desire of transit agencies to design their network by taking into account both existing and latent demand, as quality of service improves. The paper presents a bilevel optimization where the leader problem

抒情短詩

Local Search and Constraint Programming for a Real-World Examination Timetabling Problem be applied to a large set of universities, but is quite different in many aspects from the classical versions proposed in the literature..We propose both a metaheuristic approach based on Simulated Annealing and a Constraint Programming model in MiniZinc. We compare the results of the metaheuristic

Cardiac-Output

Parameterised Bounds on the Sum of?Variables in Time-Series Constraintsum of the time-series variables wrt these families of constraints. This is important in many applications, as this sum represents the cost, for example the energy used, or the manpower effort expended. We use these bounds not only to gain a priori knowledge of the overall cost of a problem, we can a

配置

A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programslems with constraints in the first and second stages. The goal of the algorithm is to predict a . (RS) for the problem such that, deterministically solving the 2SIP with the random realization equal to the RS, gives a near-optimal solution to the original 2SIP. Predicting an RS, instead of directly

含糊

Integer Programming Techniques for Minor-Embedding in Quantum Annealersical limitation has generated considerable interest, motivating efforts to design efficient and adroit minor-embedding procedures that bypass sparsity constraints. In this paper, starting from a previous equational formulation by Dridi et al. (arXiv:1810.01440), we propose integer programming (IP) t

frivolous

An Ising Framework for Constrained Clustering on Special Purpose Hardwareproblems has spurred interest in formulating key problems as Ising models, a mathematical abstraction shared by a number of these platforms. In this work, we focus on constrained clustering, a semi-supervised learning task that involves using limited amounts of labelled data, formulated as constrain

alabaster

大量殺死

Transfer-Expanded Graphs for On-Demand Multimodal Transit Systems of hubs served by high frequency buses, and passengers are connected to the hubs by on-demand shuttles which serve the first and last miles. This paper generalizes prior work by including three additional elements that are critical in practice. First, different frequencies are allowed throughout th

野蠻

Reinforcement Learning for Variable Selection in a Branch and Bound Algorithmvers is their fine-tuned heuristics. In this paper, we leverage patterns in real-world instances to learn from scratch a new branching strategy optimised for a given problem and compare it with a commercial solver. We propose FMSTS, a novel Reinforcement Learning approach specifically designed for t

cacophony

Duplex Encoding of Staircase At-Most-One Constraints for the Antibandwidth Problem An important ingredient in the success of each of these approaches is the exploitation of common constraint structures with specialized (re-)formulations, encodings or other techniques. In this paper we present a new linear SAT encoding using binary decision diagrams over multiple variable orders a