Call for papers | JSEO 2026

Context

A shared question

Each thematic area is an invitation to submit an abstract of your work, for either a talk or a poster on the day.

Used on its own, a metaheuristic, however effective it may be on certain classes of problems, quickly reaches its limits when faced with the growing diversity and complexity of today's challenges and of problems of genuine practical interest.

Bringing these methods together within collaborative and intelligent systems opens up new possibilities. By drawing on hybridisation, collaboration, cooperation and the complementary nature of their respective properties, this new paradigm overcomes the limits inherent in any single approach, taking us from the application of an isolated algorithm to an algorithmic ecosystem.

Held for the first time at the Faculty of Mathematics, the JSEO is intended as a space for interdisciplinary exchange. It is open to the whole scientific community engaged with these questions, both today and in the years ahead.

Thematic areas

The four areas in detail

The following themes give shape to the contributions we expect. They are given as an indication and not as a restriction.

Area 1

Intelligent hybridisation of optimisation methods

New hybridisation strategies across heuristics, metaheuristics and exact methods.

New hybridisation strategies and matheuristics
Combining exact methods, heuristics and metaheuristics
Adaptive hybridisation and multi-level strategies
Intelligent mechanisms for method selection

Area 2

Intelligent cooperation and collaboration (MetaStorming)

Methods that interact, exchange and reinforce one another.

Cooperation between heuristics, metaheuristics, evolutionary algorithms, exact methods and learning based approaches
Multi-agent systems and information exchange between methods
Distributed search and optimisation, parallel computing on cloud or edge infrastructure
Benchmarking protocols and reproducibility of collaborative approaches
The MetaStorming scheme, the methodological reference for this theme

Area 3

Learning, adaptation and intelligence of optimisation ecosystems

When artificial intelligence guides the search.

Self-adaptation and self-configuration of methods
Learning during the search, reinforcement learning
Artificial intelligence and machine learning to guide optimisation
Intelligent architectures and dynamic orchestration of methods
Predictive models and matheuristics

Area 4

Optimisation and decision intelligence for industrial and societal applications

Industrial, socio-economic and interdisciplinary applications.

Industry, transport and logistics, production and supply chains
Energy, environment and regional planning
Networks, services and healthcare
Socio-economic and institutional questions
Problems arising in other disciplines and interdisciplinary collaborations: other faculties, laboratories, companies
Contributions based on real data, case studies, prototypes or working solutions are particularly welcome

Requirements

How to submit

Authors and practitioners are invited to submit an abstract of their contribution, industrial feedback or interdisciplinary work.

Go to the form

Length: Between 250 and 400 words, excluding title, authors and keywords.
Required content: The abstract must set out the context, the research question, the proposed method, the results expected or obtained, and the directions for future work.
Formatting: Calibri or Times New Roman, size 11 or 12, single or 1.15 line spacing.
File: A PDF or DOCX file of at most 10 MB, named SURNAME_Firstname_abstract, uploaded through the submission form.
Keywords: Three to five keywords, separated by semicolons.
Languages: French or English.
Type of presentation: Talk or poster, at the author's choice. The scientific committee may suggest a different format.

Optimising alone is exploring. Optimising together is converging.