Article: Stable matching-driven collaborative optimisation with blockchain verification for heterogeneous supply chain networks Journal: International Journal of Reasoning-based Intelligent Systems (IJRIS) 2026 Vol.18 No.16 pp.12 - 30 Abstract: This study addresses the problem of unstable collaboration and insufficient trust in heterogeneous supply chain networks. A blockchain-enabled stable matching collaborative optimisation model is proposed, integrating multi-agent preference-based stable matching, smart contract-driven execution, and decentralised reputation constraints. The model is tested using real enterprise data covering 22 manufacturers, 18 suppliers, 12 logistics providers, and 4 financial institutions, comprising 22,567 transaction records. Simulation results show that the number of blocking pairs is reduced from 32 to 5, the cooperation stability score increases from 0.87 to 0.98, the average resource utilisation improves from 78.4% to 85.3%, transportation capacity utilisation rises from 72.1% to 80.5%, and net income increases by 60% compared to a traditional centralised model. These quantitative improvements demonstrate that the proposed model effectively enhances collaboration efficiency, system stability, and economic performance, providing a scientifically robust approach for long-term optimisation in heterogeneous supply chain networks. Inderscience Publishers - linking academia, business and industry through research

Title: Stable matching-driven collaborative optimisation with blockchain verification for heterogeneous supply chain networks

Authors: Beidi Cao

Addresses: School of Business (Law School), Chizhou University, Chizhou, 247000, China

Abstract: This study addresses the problem of unstable collaboration and insufficient trust in heterogeneous supply chain networks. A blockchain-enabled stable matching collaborative optimisation model is proposed, integrating multi-agent preference-based stable matching, smart contract-driven execution, and decentralised reputation constraints. The model is tested using real enterprise data covering 22 manufacturers, 18 suppliers, 12 logistics providers, and 4 financial institutions, comprising 22,567 transaction records. Simulation results show that the number of blocking pairs is reduced from 32 to 5, the cooperation stability score increases from 0.87 to 0.98, the average resource utilisation improves from 78.4% to 85.3%, transportation capacity utilisation rises from 72.1% to 80.5%, and net income increases by 60% compared to a traditional centralised model. These quantitative improvements demonstrate that the proposed model effectively enhances collaboration efficiency, system stability, and economic performance, providing a scientifically robust approach for long-term optimisation in heterogeneous supply chain networks.

Keywords: stable matching; blockchain; heterogeneous network of supply chain; collaborative optimisation; multi-objective decision making.

DOI: 10.1504/IJRIS.2026.154390

International Journal of Reasoning-based Intelligent Systems, 2026 Vol.18 No.16, pp.12 - 30

Received: 04 Feb 2026
Accepted: 08 Apr 2026
Published online: 25 Jun 2026 *

Title: Stable matching-driven collaborative optimisation with blockchain verification for heterogeneous supply chain networks

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