Akademik Veri Yönetim Sistemi
Canadian Journal of Civil Engineering, cilt.52, sa.5, ss.770-795, 2025 (SCI-Expanded)
Enhancing railway freight logistics efficiency is crucial for strengthening global supply chain performance, yet persistent challenges such as infrastructure limitations, operational inefficiencies, and fragmented intermodal integration hinder optimal performance. Despite its critical role in economic and environmental sustainability, limited research offers compre-hensive, universally applicable solutions for addressing these issues. This study bridges this gap by introducing a novel multicriteria decision-making framework that integrates inter-criteria correlation (CRiteria Importance Through Intercriteria Correlation (CRITIC)) and multi-objective optimization based on ratio analysis (Multi-attribute Multi-Objective Optimization based on Ratio Analysis (MULTIMOORA)) with Q-rung orthopair fuzzy sets (q-ROFSs) to handle complex and conflicting decision-making scenarios. These methods were selected for their complementary strengths. CRITIC effectively quantifies the importance of criteria by considering their interdependencies, MULTIMOORA offers robust multi-objective optimization capabilities, and q-ROFSs manage the inherent uncertainty and ambiguity of real-world logistics problems. Their integration provides a comprehensive framework capable of addressing both the complexity and uncertainty in railway freight logistics decision-making. A two-phase sensitivity analysis validates the framework’s reliability and consistency. Results indicate that “infrastructure invest-ment” ranks as the most impactful strategy, followed by “intermodal transportation”. These findings offer practical guidance for policymakers and industry leaders, providing actionable solutions to enhance operational performance and sustainability while advancing the theoretical discourse in transportation logistics.