A Quantum Approximate Optimization Algorithm Based on Blockchain Heuristic Approach for Scalable and Secure Smart Logistics Systems

【Author】 El Azzaoui, Abir; Kim, Tae Woo; Pan, Yi; Park, Jong Hyuk

【Source】HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES

【影响因子】6.558

【Abstract】Smart logistics and supply chain play can determine the success or failure of any business. The cost, time, and carbon footprint are critical elements to be considered. Smart logistics solely consume 53% of the company's income and produce up to 10% of its carbon footprint. Moreover, the time consumed in transportation and supply chains from the resource acquisition to the client contributes to the business profit. Enhancing smart logistics systems by selecting the optimal route is a hard problem even for today's supercomputers. On the other hand, Quantum-based processing and Quantum algorithms are proved to solve convoluted computation to attain a heuristic system swiftly compared with classical processing methods. Notably, Quantum approximate optimization algorithm (QAOA), as a variational Quantum algorithm for approximately solving discrete combinatorial optimization problems can be deployed into the smart logistics dilemma to improve the scalability of the system, decrease the time, thus reducing the carbon footprint and smart manufacturing system cost. Moreover, blockchain, as a secure distributed ledger, is capable of bringing the desired security to the smart logistic system. To this end, we propose an improved QAOA based on blockchain technology to improve the scalability and reduce the cost of smart logistics.

【Keywords】Quantum Approximate Optimization Algorithm; Blockchain; Smart Logistics; Supply Chain; Smart Transportation

【发表时间】2021 DEC 30

【收录时间】2022-01-09

【文献类型】期刊

【主题类别】

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