Rovie Manansala, Francis Adrian Viernes, Varsolo Sunio
University of Asia and the Pacific, Pasig City, 1605, Metro Manila, Philippines
Sustainable Logistics through Consolidation: Two-Phase Load Planning (2Ph-LPM)
for a Cross-Docking Facility in the Philippines
Introduction
Methodology
Key Results & Recommendation
The Philippine logistics sector is experiencing rapid growth, driven by increasing demand and economic activity. However, this expansion places pressure on limited transport resources, leading to inefficiencies such as underutilized truck capacity, rising costs, and operational constraints. Shipment consolidation has emerged as a key strategy to improve utilization and resource efficiency. Despite its potential, many studies rely on theoretical models with limited real-world application. This study addresses this gap by analyzing actual operational data from a logistics service provider’s cross-docking facility in the Philippines. Initial diagnostics revealed a high proportion of underutilized dispatches and limited consolidation (Figure 1).
Phase 1: Mixed Integer Linear Programming is the main algorithm used in the first phase with the objective of maximizing shipment assignment and utilization quality.
Phase 2: A fallback mechanism using Greedy Heuristic algorithm attempted to recover shipments unassigned in Phase 1, inserting them to partially utilized trucks.
What-If Analysis: Testing the model under different demand scenarios beyond a single-point estimate to demonstrate stability.
Operational Metric | Baseline | Optimized | Implications |
Underutilized Trips (≤50% Truck Capacity) | 45 – 50% | 18.67% of dispatches (394 in total) | Reduced Waste: Efficient usage of truck space, significantly lowering cost-per-unit delivered |
Severely Utilized Trips (>90% Truck Capacity) | 30 – 35% | 40.99% of dispatches (865 in total) | Increased Asset Utilization: Maximized load density, improving asset profitability |
Single-order truck dispatches | 2091 | 324 | 84.5% reduction: Increased consolidation directly lowers handling costs and increases operational efficiency per order |
Total Truck dispatches | 6,448 | 2,110 | 67.3% Reduction: Can translate to substantial savings on fuel, labor cost, and vehicle maintenance |
Resource Usage (Truck Used/Available) | N/A | Median Weekly Usage Rate of 28.57% | Capital Efficiency: Reduced truck usage frees up capital or reducing the need for acquiring new vehicles |
The 2Ph-LPM demonstrated significant improvements in truck utilization and operational efficiency (Figure 3 and Table 1). Results show a substantial reduction in total truck dispatches, from 6,448 to 2,110, indicating strong potential for cost savings in fuel, labor, and maintenance. The utilization profile improved markedly, with highly utilized trips accounting for 40.99% of dispatches, while underutilized trips decreased to 18.67%. The model also reduced single-order dispatches and increased multi-order consolidation, enhancing resource efficiency. Despite these gains, the model achieved an assignment rate of around 70%, reflecting a trade-off between strict constraint adherence and full shipment allocation. Overall, the hybrid optimization approach proved effective in balancing solution quality and computational efficiency, while highlighting opportunities for future improvements in assignment completeness and operational flexibility.
The study utilizes three months of real operational data from a logistics service provider’s transport management system, including order-level and dispatch-level records. A hybrid Two-Phase Load Planning Model (2Ph-LPM) is developed, combining Mixed Integer Linear Programming (MILP) for initial assignment with a greedy heuristic fallback to allocate remaining shipments (Figure 2).
Figure 1
Table 1
Figure 3
Figure 2