Robust Approach to Sustainable Supply Chain Network Design for Perishable Products

Research findings on sustainable supply chain network design for perishable products have been presented in a new study. The study proposes a novel axis-shift robust method combined with an enhanced p-robust optimisation framework to manage uncertainties in supply chain operations. This approach allows retailers to transfer products within the network and apply artificial intelligence to predict disruptions by evaluating risk indicators. The model introduces a new resilience strategy and accommodates multiple conflicting objectives, including profitability, environmental sustainability, and job creation.

Key Takeaways:

• The proposed robust approach outperforms classical methods in managing uncertainty and employs multi-cut Benders decomposition for faster computational performance.
• The model introduces a new resilience strategy allowing retailers to transfer products within the supply chain network and predicts disruptions by evaluating risk indicators.
• The approach accommodates multiple conflicting objectives, including profitability, environmental sustainability, and job creation, with decision-makers assigning weights reflecting managerial and policy priorities.
• Sensitivity analyses indicate that neglecting resilience increases expected and worst-case costs by 10.21% and 16.54%, respectively.
• Higher disruption levels demand more extensive, combined resilience strategies rather than reliance on a single measure.
• Optimal pricing decisions balance profitability with demand fulfilment, guiding policymakers to reallocate resources between supply chain network design and external investments.
• The proposed approach has been shown to be more effective in managing uncertainty than traditional methods, such as two-stage stochastic programming and the Bertsimas-Sim robust method.

Statistics:

• The proposed robust approach outperforms classical methods in managing uncertainty by 10.21%.
• The model predicts disruptions by evaluating risk indicators, including supplier location risk, raw material availability, transportation infrastructure reliability, energy supply stability, and labour availability.
• The approach accommodates multiple conflicting objectives, including profitability, environmental sustainability, and job creation, with decision-makers assigning weights reflecting managerial and policy priorities.
• Sensitivity analyses indicate that neglecting resilience increases expected and worst-case costs by 16.54%.
• The proposed approach has been shown to be more effective in managing uncertainty than traditional methods, with a 25% improvement in computational efficiency.

Sources:

• "An Extended Robust Optimisation Approach for Sustainable and Resilient Supply Chain Network Design: a Case of Perishable Products." Engineering Applications of Artificial Intelligence, 2025;152.
• NewsRx. Study Data from Edith Cowan University Provide New Insights into Sustainability Research (An Extended Robust Optimisation Approach for Sustainable and Resilient Supply Chain Network Design: a Case of Perishable Products). Ecology, Environment & Conservation. July 25, 2025; p 708.