Search Results for author:
Found 14 papers, 5 papers with code
Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection
The branch-and-bound algorithm based on decision diagrams introduced by Bergman et al. in 2016 is a framework for solving discrete optimization problems with a dynamic programming formulation.
Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model
We use it to simulate the spread of a new variant across European countries, and to assess the effectiveness of unilateral and multilateral travel bans.
Improving the filtering of Branch-And-Bound MDD solver (extended)
This paper presents and evaluates two pruning techniques to reinforce the efficiency of constraint optimization solvers based on multi-valued decision-diagrams (MDD).
Impact of weather factors on migration intention using machine learning algorithms
A growing attention in the empirical literature has been paid to the incidence of climate shocks and change in migration decisions.
Using an interpretable Machine Learning approach to study the drivers of International Migration
a traditional model, and 2) using PDP we are able to gain additional insights on the specific effects of the migration drivers.
An LSTM approach to Forecast Migration using Google Trends
Being able to model and forecast international migration as precisely as possible is crucial for policymaking.
An aggregate learning approach for interpretable semi-supervised population prediction and disaggregation using ancillary data
Census data provide detailed information about population characteristics at a coarse resolution.
Testing Global Constraints
Every Constraint Programming (CP) solver exposes a library of constraints for solving combinatorial problems.
REPETITA: Repeatable Experiments for Performance Evaluation of Traffic-Engineering Algorithms
In this paper, we propose a pragmatic approach to improve reproducibility of experimental analyses of traffic engineering (TE) algorithms, whose implementation, evaluation and comparison are currently hard to replicate.
Networking and Internet Architecture
Mining a Sub-Matrix of Maximal Sum
Two different algorithms are proposed in order to exploit the highlighted characteristics of the problem: a CP approach with a global constraint (CPGC) and mixed integer linear programming (MILP).
A Visual Web Tool to Perform What-If Analysis of Optimization Approaches
In Operation Research, practical evaluation is essential to validate the efficacy of optimization approaches.
Compact-Table: Efficiently Filtering Table Constraints with Reversible Sparse Bit-Sets
In this paper, we describe Compact-Table (CT), a bitwise algorithm to enforce Generalized Arc Consistency (GAC) on table con- straints.
Parallel Strategies Selection
EPS proposes to solve a problem by decomposing it in a lot of subproblems and to give them on-demand to workers which run in parallel.
An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming
Detailed experiments show how this approach outperforms existing CP as well as specialized systems for SPM, and that the gain in efficiency translates directly into increased efficiency for other settings such as mining with regular expressions.
