Title: Robust optimisation of the problem of dynamic localisation of modular mobile facilities in a hybrid network for an uncertain environment

Authors: Charifa Fergani; Adiba El Bouzekri El Idrissi; Suzanne Marcotte; Abdelowahed Hajjaji

Addresses: Department of Science of Industrial Technologies (STIN), National School of Applied Sciences, Chouaïb Doukkali University, El Jadida, Morocco ' Department of Science of Industrial Technologies (STIN), National School of Applied Sciences, Chouaïb Doukkali University, El Jadida, Morocco ' Department of Management and Technology, School of Management Sciences, University of Quebec, Montreal, Canada ' Department of Science of Industrial Technologies (STIN), National School of Applied Sciences, Chouaïb Doukkali University, El Jadida, Morocco

Abstract: Production facility location is a critical aspect of supply chain management, as it enables decision makers to determine the optimal location for production to meet customer demand effectively both strategically and tactically. Given the highly dynamic nature of today's markets, taking into account uncertain parameters can lead to more robust decision making under uncertain conditions. This paper presents a robust optimisation approach to solve the dynamic location problem of mobile modular facilities in a hybrid network of localisations considering stochastic demand. The objective of the model is to optimise the total expected cost, the cost variability due to demand uncertainty, and the penalty for demand infeasibility. The study illustrates the efficiency and robustness of the proposed model with numerical results from a case study in the chemical industry. Additionally, the study analyses the trade-off between the robustness of the model and that of the solution.

Keywords: robust optimisation; demand uncertainty; modular mobile facilities; hyperconnected network; MIP.

DOI: 10.1504/IJLSM.2026.151739

International Journal of Logistics Systems and Management, 2026 Vol.53 No.2, pp.265 - 283

Received: 17 Jul 2023
Accepted: 23 Jul 2023
Published online: 18 Feb 2026 *

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