type
concept
created
Tue Apr 07 2026 02:00:00 GMT+0200 (Central European Summer Time)
updated
Tue Apr 07 2026 02:00:00 GMT+0200 (Central European Summer Time)
sources
raw/articles/PRD
tags
container optimization freight fill-suggestions competitive-moat

Container Fill Optimization

abstract
When a buyer selects a partial load, the platform detects the gap and suggests compatible surplus from other mills to fill the container, displaying an LCL vs FCL freight comparison with net savings -- a capability no email/Excel broker can replicate.

Overview

Container fill optimization is the platform's primary competitive moat. It extends container assembly by actively detecting when a buyer's selected items only partially fill a container and suggesting additional compatible surplus to complete the load. The buyer sees a side-by-side comparison of Less-than-Container-Load (LCL) partial shipping costs versus Full Container Load (FCL) costs, with net savings displayed.

Two Flows

  1. Full container: A mill's lot fills ~25 MT. Straightforward order, no fill needed.
  2. Partial load: A mill has e.g. 12 MT. The platform finds 13+ MT of compatible surplus from other mills, ranked by spec match + price.

Fill Suggestion Algorithm

The algorithm follows these steps:

  1. Calculate container gap: From the primary items and container type, determine current_weight, gap_mt, utilization_pct, and whether the container is full or needs filling.

  2. If full: Return empty -- no fill needed.

  3. Query candidates:

    • Status must be available
    • Must NOT be from the same mills as the primary items
    • Must match at least one of the buyer's active BuyerSpecs (paper_type, GSM range, grades, max_price)

  4. Check product compatibility for each candidate:

    • Same paper group as primary items (containerboard, board, specialty, tissue)
    • Grade gap <= 1 (A+B allowed, A+C rejected)
    • Food contact: if primary items require it, candidate must too

  5. Score each candidate (0-100 scale):

    • Base score: 50
    • Paper type exact match with primary: +20
    • GSM closeness to primary items: +15 (linear scale, 0 if difference >= 100 GSM)
    • Price advantage vs buyer's max price: +15

  6. Rank by score, cap each candidate's max_quantity to the remaining gap, return top 10 suggestions.

Freight Comparison Display

The platform presents a clear cost comparison:

LCL (Partial) FCL (Full Container)
Weight 12.00 MT 26.00 MT
Freight rate $180/MT (LCL per-ton rate) $4,200 flat (FCL container rate)
Freight cost $2,160 $4,200
Per MT freight $180.00 $161.54

Net Savings Calculation

The platform does not blindly recommend filling every container. It calculates net savings:

net_savings = freight_savings - extra_product_cost

If filling the container costs $8,450 in extra paper but saves only $1,680 in freight, net_savings = -$6,770 (not worth it). The platform only recommends fill when net savings > 0 or when freight per MT drops significantly.

FreightRate Lookup Table

Freight comparisons are powered by a maintained rate table:

Field Description
origin_region Region code (EU, ASIA, LATAM, NA, MENA, AFRICA, OCEANIA)
destination_region Region code
container_type 20ft, 40ft, or 40ft_hc
fcl_rate Full container flat rate (USD)
lcl_rate_per_mt LCL rate per metric ton (USD)
effective_date / expiry_date Rate validity period
is_active Boolean

Unique constraint: (origin, destination, container_type) WHERE is_active. This ensures one active rate per route per container type.

Benchmark Freight Rates

Route 20ft 40ft 40ft HC
Intra-EU $800 $1,200 $1,300
EU to North Africa $1,500 $2,200 $2,400
EU to South America $2,500 $3,800 $4,000
EU to Middle East $1,800 $2,800 $3,000
Asia to South America $3,000 $4,500 $4,800
Asia to EU $2,000 $3,200 $3,500

API Endpoint

POST /api/container-proposals/fill-suggestions/
Body: { surplus_item_ids: [uuid], buyer_id: uuid, container_type: "40ft" }

Response includes: container_gap details, ranked suggestions (up to 10), freight_comparison_current (LCL vs FCL at current weight), freight_comparison_if_filled (projected with suggested items), extra_product_cost, and net_savings.

Why This Is the Competitive Moat

No email/Excel broker can replicate this because:

Sources

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