2026-08-11T06:33:09Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:23688 2025-11-12T12:50:45Z ddc:004 open_access

An Architecture for Composite Combinatorial Optimization Solvers Chrit, Khalil Baffier, Jean-François Patinho, Pedro Abreu, Salvador Hybrid Metaheuristics DSL In this paper, we introduce elements for MoSCO, a framework for building hybrid metaheuristic-based solvers from a collection of reusable base components. The framework is implemented in Julia and provides a modular architecture for composing solvers through a pipeline-based approach. The modular design of MoSCO supports the creation of reusable components and adaptable solver strategies for various Constraint Satisfaction Problems (CSPs) and Constraint Optimization Problems (COPs). We validate MoSCO’s utility through practical examples, demonstrating its effectiveness in reconstructing established metaheuristics and enabling the creation of novel solver configurations. This work lays the foundation for future developments in automated solver construction and parameter optimization. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Khalil Chrit and Jean-François Baffier and Pedro Patinho and Salvador Abreu 2025 Is Part Of OASIcs, Volume 135, 14th Symposium on Languages, Applications and Technologies (SLATE 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.SLATE.2025.8 urn:nbn:de:0030-drops-236885 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2025.8 eng https://creativecommons.org/licenses/by/4.0/legalcode