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The Physical Internet (PI)-enabled hyperconnected order-to-delivery system (OTD) provides new solutions for sustainable supply chains from production perspectives. In this system, a PI-enabled hyperconnected manufacturing system is more closely tied with other functions through Internet-of-Things (IoT)-enabled machines for communication. In the OTD, the PI-enabled hyperconnected production&#x2013;distribution system (PI-H) is modelled by multi-objective mixed-integer-nonlinear programming to evaluate sustainability. We develop an improved reference-point based non-dominated sorting genetic algorithm (I-NSGAIII) to solve practical-scale PI-enabled hyperconnected production-distribution scheduling problems, with the problem-specific solution expression and dynamic programming, subproblem-guided crossover and mutation strategies, and adaptive evolution mechanisms. I-NSGAIII&#x2019;s performance advantages and PI-H&#x2019;s sustainable advantages are validated through extensive experiments.

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Solving the Sustainable Automobile Production-Distribution Joint Optimization in the Physical Internet-Enabled Hyperconnected Order-to-Delivery System by I-NSGAIII