A Dual-Spread Opportunity VAM for Transportation Problems under Deterministic Cost Environments

Transportation challenges often occur in logistics and supply chain management, necessitating the movement of commodities from several sources to different destinations while minimizing transportation expenses. This paper proposes a Dual-Spread Opportunity VAM (DSO-VAM) for obtaining high-quality initial basic feasible solutions to transportation problems. The method is motivated by a revised VAM framework that improves classical penalty-based allocation by modifying row and column penalties. To address some limitations of existing methods, the proposed method combines dual-spread row and column penalties with an opportunity-based decision score that measures the future regret of postponing a low-cost allocation. A fixed weighting mechanism is introduced so that the relative influence of cost spread and allocation pressure changes dynamically throughout the solution process. Numerical examples show that DSO-VAM matches or improves upon the solutions obtained by NWCM, MCM, VAM, and the Revised-VAM. The proposed framework preserves computational simplicity while providing a more flexible and globally informed allocation rule for transportation optimization.