A Plithogenic–Neutrosophic Carbon Budget and Contradiction Model for Sustainable Logistics Enterprises under Carbon Peak and Neutrality Targets

The achievement of dual carbon goals carbon peaking followed by carbon neutrality demands decision frameworks that can simultaneously address multi-attribute contradictions and uncertainty in environmental performance data. This paper introduces the Plithogenic–Neutrosophic Dual-Carbon Green Flow (PN-DCGF) model, a novel mathematical methodology that fuses plithogenic set theory with neutrosophic measure, integral, and probability to optimize green logistics strategies under complex sustainability constraints. Plithogenic operators aggregate performance attributes, such as emission reduction, cost variation, renewable energy share, and policy compliance, while explicitly weighting the contradiction degree of each attribute value relative to a dominant sustainability value. Neutrosophic measures express carbon budgets as ordered triples determinate allowance, indeterminate margin, and determinate overshoot and neutrosophic integrals compute compliance momentum over policy windows with uncertain limits or values. Plithogenic probability is employed to model multiple likelihoods of operational outcomes conditioned on attribute values. The framework enforces a dual-goal feasibility envelope, ensuring that neutrosophic emissions never exceed the carbon budget triple according to monotonicity and additivity rules. A fully calculated case study on a multimodal freight network illustrates the model’s capacity to rank strategies, quantify compliance under uncertainty, and evaluate scenario-based goal attainment. Results demonstrate that PN-DCGF provides a rigorous, contradiction-aware, and uncertainty-resilient decision basis for sustainable logistics planning aligned with carbon peaking and neutrality objectives.