INTEGRATING SIMULATION AND OPTIMIZATION FOR SUSTAINABILITY ASSESSMENT IN COMPLEX SUPPLY CHAINS: A UNIFIED FRAMEWORK WITH AI

Anastasiia Rozhok, Khursheed Ahmad, Roberto Revetria

Abstract


The increasing complexity of global supply chains and the rising emphasis on sustainability require innovative methodologies to assess and optimize operational performance. This paper introduces a unified framework integrating simulation, optimization, and artificial intelligence (AI) to evaluate and enhance the sustainability of complex supply chains. The framework leverages AnyLogistiX’s simulation (SIM) and optimization (OPT) modules to model existing supply chain configurations, calculate sustainability indices, and identify improvements through AI-generated scenarios. The proposed approach begins with a detailed examination of the current state of supply chains, emphasizing the predominance of road transport and centralized logistics. It then integrates the sustainability index, derived from a previous study, as a key metric for performance evaluation. AI’s capabilities are harnessed to generate innovative scenarios that address sustainability challenges, such as reducing carbon emissions, traffic congestion, and dependency on centralized hubs. This study applies the framework to a European distribution supply chain, comparing an AS-IS scenario with an AI-generated TO-BE configuration. The TO-BE scenario features the integration of ro-ro shipping and intelligent replenishment systems, showcasing significant improvements in sustainability metrics. The comparative analysis underscores the transformative potential of AI-driven solutions in achieving sustainable supply chain operations. 

Keywords


Sustainability assessment, supply chain, supply chain modelling, simulation, AnyLogistix.

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References


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DOI: https://dx.doi.org/10.21622/MARLOG.2025.14.1.83

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The International Maritime Transport and Logistics Journal (MARLOG)

E-ISSN: 2974-3141
P-ISSN: 2974-3133

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