Sabino Francesco Roselli
Sabino Roselli is a joint postdoctoral researcher between the Automation group and the Production Maintenance group, focusing his research on optimal and sub-optimal scheduling of large-scale industrial systems by means of classic optimization methods combined with machine learning.
Showing 14 publications
Integrating Machine and Quality Data for Predictive Maintenance in Manufacturing System
Conflict-free electric vehicle routing problem: an improved compositional algorithm
A Compositional Algorithm for the Conflict-Free Electric Vehicle Routing Problem
Leveraging Conflicting Constraints in Solving Vehicle Routing Problems
Solving the conflict-free electric vehicle routing problem using SMT solvers
On the Use of Equivalence Classes for Optimal and Suboptimal Bin Packing and Bin Covering
An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem
Comparison of Exact and Approximate methods for the Vehicle Routing Problem with Time Windows
Compact Representation of Time-Index Job Shop Problems Using a Bit-Vector Formulation
On the use of equivalence classes for optimal and sub-optimal bin covering
SMT solvers for flexible job-shop scheduling problems: A computational analysis
SMT Solvers for Job-Shop Scheduling Problems: Models Comparison and Performance Evaluation
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Showing 2 research projects
Integrated Manufacturing Analytics Platform för Prediktivt Underhåll med Iot.