Real-time large-scale supplier order assignments across two-tiers of a supply chain with penalty and dual-sourcing

TL;DR

This paper introduces a scalable, real-time optimization model for large-scale, multi-tier supplier order allocation with penalty and dual-sourcing constraints, demonstrating significant cost savings in a real-world manufacturing case.

Contribution

It presents a novel mixed-integer programming approach for large-scale supply chain order allocation, outperforming genetic algorithms and enabling practical deployment in industry.

Findings

Mixed-integer programming outperforms genetic algorithms in solving large-scale SSOA.

Application to a real manufacturing case achieved over 10% procurement cost reduction.

Model successfully deployed in a large international sourcing conference.

Abstract

Supplier selection and order allocation (SSOA) are key strategic decisions in supply chain management which greatly impact the performance of the supply chain. Although, the SSOA problem has been studied extensively but less attention paid to scalability presents a significant gap preventing adoption of SSOA algorithms by industrial practitioners. This paper presents a novel multi-item, multi-supplier double order allocations with dual-sourcing and penalty constraints across two-tiers of a supply chain, resulting in cooperation and in facilitating supplier preferences to work with other suppliers through bidding. We propose Mixed-Integer Programming models for allocations at individual-tiers as well as an integrated allocations. An application to a real-time large-scale case study of a manufacturing company is presented, which is the largest scale studied in terms of supply chain size and number of variables so far in literature. The use case allows us to highlight how problem formulation and implementation can help reduce computational complexity using Mathematical Programming (MP) and Genetic Algorithm (GA) approaches. The results show an interesting observation that MP outperforms GA to solve SSOA. Sensitivity analysis is presented for sourcing strategy, penalty threshold and penalty factor. The developed model was successfully deployed in a large international sourcing conference with multiple bidding rounds, which helped in more than 10% procurement cost reductions to the manufacturing company.