EURO 2024 Copenhagen
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928. Sustainable Routing and Perishable Inventory Optimization under Demand Uncertainty for a 2- stage Divergent Supply Chain: A MILP-Based Hybrid Modelling Approach

Invited abstract in session TA-24: Sustainability in Vehicle Routing, stream Sustainable Supply Chains.

Tuesday, 8:30-10:00
Room: 83 (building: 116)

Authors (first author is the speaker)

1. Devansh Rai
Department of Management Studies, Indian Institute of Technology Madras
2. Chandrasekharan Rajendran
Department of Management Studies, Indian Institute of Technology Madras

Abstract

In the dynamic landscape of perishable product management, efficient inventory optimization is crucial for minimizing waste and maximizing profitability. This research focuses on enhancing inventory optimization for perishable products in a 2-stage divergent supply chain involving a distributor and multiple retailers. The study proposes a novel approach that integrates sustainable inventory routing and inventory ordering policies to address challenges in inventory management. The model approach is a two-stage stochastic optimization problem with a multi-period perspective. The framework considers price-dependent demand, perishable product characteristics, back-ordering at the distributor, lost-sales at the retailers, demand uncertainty, age-based markdown pricing, and distributor-led inventory rationing. The research introduces a comprehensive policy and routing framework combining innovative inventory ordering policies and routing strategies. The proposed hybrid policy will be benchmarked against established inventory models, including (s,Q), (s,S), Haijema (s,S,q,Q), and other continuous review policies, all integrated with inventory routing. The new inventory policy can facilitate informed ordering decisions, preventing overstocking and understocking, thereby addressing real-world uncertainties and practical constraints in perishable product supply chains. Additionally, a heuristic method can be developed to provide efficient solutions within a limited timeframe.

Keywords

Status: accepted

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