éric 🚲 🇪🇺 Jul 14, 2025

New article published today in the Computers & Chemical Engineering journal: *A multi-agent system for hybrid optimization*. This paper is based on the work presented last year at the European Symposium on Computer Aided Process Engineering (ESCAPE 34) conference.

One key lesson I took away from this work: how easy it is to write efficient and effective multiprocessing code in Julia. And how much fun it is actually. 🙂

#MultiAgentSystem #Agents #Optimization #HybridOptimization #ProcessSystemsEngineering #CAPE #PSE #JuliaLang

https://doi.org/10.1016/j.compchemeng.2025.109258

éric 🚲 🇪🇺 Jan 30, 2025

New post-doctoral research position in my group at University College London (#UCL), looking at the use of **optimization for the design of dynamic and flexible processes for electronic waste**, in collaboration with researchers in multi-phase and micro-channel flow experiments for process intensification and in model identification for the development of dynamic models. The eventual deliverable of this project is a demonstrator process with a digital twin. External collaboration includes both industry and two local councils, Newham Council in London and West Sussex County Council.

Closing date: 13 February 2025

#ChemicalEngineering #ProcessSystems #ProcessSystemsEngineering #PSE #PostDoctoralResearch #Optimization #eWaste #ProcessDesign #DigitalTwin

https://www.ucl.ac.uk/work-at-ucl/search-ucl-jobs/details?nPostingId=12911&nPostingTargetId=31636&id=Q1KFK026203F3VBQBLO8M8M07

UCL – University College London

UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

Work at UCL
éric 🚲 🇪🇺 Jan 17, 2025

## New paper on arXiv

*A multi-agent system for hybrid optimization*

by me and colleagues at #UCL #ChemicalEngineering.

https://arxiv.org/abs/2501.09563

#agents #MultiAgentSystem #optimization #PSE #ProcessSystemsEngineering #HybridOptimization #JuliaLang

A Multi-agent System for Hybrid Optimization

Optimization problems in process engineering, including design and operation, can often pose challenges to many solvers: multi-modal, non-smooth, and discontinuous models often with large computational requirements. In such cases, the optimization problem is often treated as a black box in which only the value of the objective function is required, sometimes with some indication of the measure of the violation of the constraints. Such problems have traditionally been tackled through the use of direct search and meta-heuristic methods. The challenge, then, is to determine which of these methods or combination of methods should be considered to make most effective use of finite computational resources. This paper presents a multi-agent system for optimization which enables a set of solvers to be applied simultaneously to an optimization problem, including different instantiations of any solver. The evaluation of the optimization problem model is controlled by a scheduler agent which facilitates cooperation and competition between optimization methods. The architecture and implementation of the agent system is described in detail, including the solver, model evaluation, and scheduler agents. A suite of direct search and meta-heuristic methods has been developed for use with this system. Case studies from process systems engineering applications are presented and the results show the potential benefits of automated cooperation between different optimization solvers and motivates the implementation of competition between solvers.

arXiv.org
éric 🚲 🇪🇺 May 24, 2024

New paper just out: *A multi-agent system for hybrid optimization*, to be presented at the #ESCAPE34 #PSE24 conference in Florence.

#optimization #HybridOptimization #ProcessSystemsEngineering #JuliaLang #MultiAgentSystem