Author

Andrei Tomut

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Conference Open access Aug 2026

Preserving Optimization Algorithm Expertise by means of Executable Algorithm Knowledge Graphs: A Worked Example on the TSP

Procedural knowledge and expertise in algorithm design are usually hidden in source code and reproduced for each new optimization problem. In this work, we deal with the important question of how to store and encode this expertise in a reusable way. This is done by so-called Generative Executable Algorithm Knowledge Gr...

Camilo Chacón Sartori, José H. García, Andrei Tomut et al. · Conference on Computer Scien... · 0 citations

#artificial intelligence Preprint Mar 2026

Transferable knowledge graphs with executable learned operators for algorithm design

This work introduces Generative Executable Algorithm Knowledge Graphs (GEAKG), a representation in which this knowledge is stored as a generative, executable, transferable graph: typed nodes hold validated operators, edges encode admissible compositions, and learned edge weights record effective sequences.

Camilo Chacón Sartori, Jos'e H. Garc'ia, Andrei Tomut et al. · 0 citations