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

Abstract

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. 

DOI: 10.5281/zenodo.16887970