Adaptive Neutrosophic Goal Programming for SoH-Aware Tri-Objective Closed-Loop Supply Chain Optimisation under Battery Degradation Uncertainty

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Offers a novel neutrosophic goal programming approach for multi-objective supply chain optimization under battery degradation uncertainty.

🏢実務担当者:Provides SoH thresholds and cost-emission ratios for managing battery fleet operations and reducing carbon footprint.

<title>Abstract</title> <p> Battery-powered logistics networks face a critical challenge: progressive degradation of battery State-of-Health (SoH) contracts distribution capacity, reduces overall system throughput, and increases supply shortages while introducing significant uncertainty in cost and emission parameters. This study develops a multi-period tri-objective closed-loop supply chain (CLSC) model that integrates SoH directly into distribution capacity ( <italic>Cap_d(k) = 280 × SoH</italic> ) and operational budget constraints. All uncertain cost and emission parameters are represented as adaptive Single-Valued Triangular Neutrosophic Numbers (SVTNN), with membership degrees updated dynamically based on SoH, State-of-Charge (SoC), and acoustic emission signals. The model minimises total logistics cost (Z₁), carbon emissions (Z₂), and supply shortage (Z₃) simultaneously. Three solution approaches are employed: weighted-sum scalarisation across seven SoH levels (1.00 to 0.73), epsilon-constraint Pareto frontier generation, and Neutrosophic Goal Programming (NGP) with constrained aspiration levels. Results show that as SoH declines from 1.00 to 0.73, total cost and emissions decrease by approximately 27% due to reduced operational scale, while supply shortage increases from 975 to 1,052 units (shortage rate rising from 83.6% to 90.2%). The NGP formulation consistently achieves zero deviation from aspiration levels and yields superior emission performance compared to the weighted-sum method. The study provides actionable insights, including an invariant cost-emission ratio ( <italic>Z₂/Z₁ ≈ 0.0912 kg CO₂/₹</italic> ), SoH thresholds for intervention (0.80 and 0.73), and a clear quantification of the emission-shortage trade-off. The proposed SVTNN-NGP framework offers a robust decision-support tool for sustainable battery-powered logistics under degradation uncertainty. </p>

• Research Square https://doi.org/10.21203/rs.3.rs-9613524/v2first seen 2026-05-23 04:31:32 · last seen 2026-06-02 04:21:54