Operational transport planning in an automobile supply chain: an interactive fuzzy multi-objective approach

We propose a novel fuzzy multi-objective linear programming model (FMOLP) for the supply chain transport planning problem at the operational level that considers various conflicting objectives simultaneously as well as the imprecise nature of sonic critical parameters such as capacity levels. The proposed model enables improved procurement process optimizing the use of transport resources and inventory levels. We also present an interactive solution methodology to convert this FMOLP model into an auxiliary crisp single-objective linear model and to find a preferred compromise solution in an interactive fashion. We validated the proposed model and the solution methodology in a real-world automobile supply chain. The computational results indicate that the proposed approach outperforms the heuristic decision-making procedure spreadsheet-based which is actually applied in the automobile supply chain under study.