High Logistics Costs (Optimisation)

Problem Statement

The high cost and inefficiency of transporting produce due to suboptimal route planning, underutilized vehicle capacity, and lack of organised back-haul opportunities contribute significantly to the final consumer price.

Innovation Opportunities

• Optimised Logistics and Route Planning Platforms: AI/ML-driven platforms that consolidate loads from multiple farmers/FPOs and generate the most efficient routes, reducing fuel costs and time.
• Back-haul/Reverse Logistics Matching Tools: Digital solutions to match agricultural transport vehicles with return loads (e.g., inputs, packaging) to eliminate empty runs.

Use Case Example

A logistics startup uses an algorithm to schedule a single temperature-controlled truck to collect produce from four different FPOs along a national highway route, consolidating the load efficiently for the metropolitan market.