Multi-modal multi-trip supply chain model aided by smart contract victim tracking - An innovative pathway to disaster management under uncertainty

【Author】 Roushan, Alisha; Das, Amrit; Dutta, Anirban; Bera, Uttam Kumar

【Source】APPLIED SOFT COMPUTING

【影响因子】8.263

【Abstract】This study addresses the complex challenges of post-earthquake rescue operations, using the recent earthquake in Turkey as a reference case. It focuses on developing an optimized model for scenarios with acute vehicle shortages, aiming to minimize both operational costs and response time during the critical initial phase of disaster relief. The proposed solution is built upon a robust mathematical framework that employs aerial vehicles for post-disaster area assessment, resource allocation, and the relocation of critically injured victims. The model leverages a soft computing approach, integrating the Weighted Sum Method (WSM) and Neutrosophic Compromise Programming (NCP). To enhance decision-making under uncertainty, the framework incorporates hexagonal type-2 fuzzy defuzzification, a technique grounded in soft computing principles. Results demonstrate the effectiveness of this approach: the NCP method achieved a response time of 213 min (3.55 h) and a cost of Rs 821,026.5, compared to 217.5 min (3.62 h) and Rs 820,860.3 for the WSM method-both successfully coordinating the rescue of 1,450 victims through efficient deployment of drones and helicopters. In addition, the study introduces a decentralized Ethereum-based smart contract to securely store and retrieve critical victim information. Validated through rigorous unit testing, the contract ensures data transparency and integrity, executing at a cost of 0.00379246 Ether. This blockchain-enabled feature complements the core optimization model, supporting real-time, tamper-proof data handling. To further validate the model's applicability, a second real-life numerical example based on the recent Sikkim cloudburst is analyzed. The findings reinforce the model's adaptability and practical value. The managerial implications of this research highlight the importance of soft computing-driven decision support, proactive contingency planning, and the integration of intelligent technologies in disaster response. This holistic framework - combining soft computing methodologies, advanced optimization models, and blockchain technology - offers an innovative and scalable solution for enhancing the resilience and efficiency of disaster management supply chains.

【Keywords】Hexagonal type-2 fuzzy set; Critical value reduction method; Solid transportation problem; Neutrosophic compromise programming; Smart contract; Supply chain management

【发表时间】2025 DEC

【收录时间】2025-09-06

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