Disrupt the network. Find the recovery plan.
| Consignment | Corridor | Gateway | Arrival / promise | Service | Modelled cost | Decision |
|---|
A decision model, with its assumptions visible. Synthetic shipments, illustrative costs and hypothetical disruptions. This is an independent portfolio prototype, not a live tracking system.
The model, the trade-offs, and what it cannot tell you.
MERIDIAN explores that question for a hypothetical UAE freight forwarder. Twelve container consignments move from Shanghai or Mumbai to Dubai or Riyadh. A disruption delays the primary gateway or the road border. The planner can reroute selected consignments, subject to a shared budget and a shared capacity limit.
Created by Kamil Zakir Hussain as an independent supply chain portfolio project, with AI-assisted implementation. It is not affiliated with an employer or university and makes no claim of operational deployment.
The service-cost proxy is AED 500 per late day for priority orders and AED 250 for standard orders. It represents a hypothetical commercial consequence, not a quoted penalty or an accounting expense.
Arrival promises are evaluated as a cost consequence. They are not hard constraints, so a valid plan can still deliver late.
A multiple-choice knapsack dynamic programme evaluates route choices across all 12 consignments. Its state is budget used and capacity used. Transport premiums are whole multiples of AED 100, so the AED 100 budget units do not round away valid choices.
The winning plan has the lowest objective value. Ties favour lower extra spend, then lower capacity consumption. For this dataset, the full choice space is only 2¹² = 4,096 plans.
Recovery value = disrupted network cost with no rerouting − cost of the chosen recovery plan. It is a modelled comparison, never evidence of realised savings.
Extra transport spend is measured against the original route's base transport cost. Cost totals also include the holding and late-service proxies. All amounts are in AED; taxes and duties are excluded.
| Corridor | Primary route | Base cost / time | Alternative | Extra cost / time |
|---|---|---|---|---|
| Shanghai → Dubai | Jebel Ali → Dubai | AED 5,400 / 18 days | Sohar → Dubai | AED 1,500 / +3 days |
| Mumbai → Dubai | Jebel Ali → Dubai | AED 3,800 / 8 days | Sohar → Dubai | AED 1,200 / +2 days |
| Mumbai → Riyadh | Jebel Ali → UAE–Saudi border → Riyadh | AED 5,600 / 12 days | Dammam → Riyadh | AED 1,800 / +2 days |
Four consignments per corridor. Promised arrivals have 1, 3, 5 and 7 days of slack above the primary route's base time. The first two are priority orders; the remaining two are standard.
Disruption logic. The Jebel Ali delay applies to every primary route. The UAE–Saudi delay additionally applies to the primary Riyadh route. Alternate routes avoid these two modelled shocks. Other border procedures and normal transport time are included in their illustrative base times.
Limitations. No live carrier feeds, sailing schedules, customs validation, booking lead times, gateway-specific capacity limits or spillover congestion. No stochastic demand, splitting, commodity restrictions, storage limits, emissions estimates or contractual penalty rules. Rerouting is assumed possible before gateway commitment. Gateway capacity is a shared modelling simplification, not observed availability. Verify every alternative with carriers and customs partners before an operational decision.
Designed an interactive logistics scenario lab to evaluate disruption recovery across three illustrative Asia–GCC corridors. Modelled 12 synthetic container consignments, port and border delays, and alternative gateway choices. Implemented constrained route optimisation to compare transport cost, late-delivery exposure and recovery value under a fixed budget and capacity limit. Independent portfolio prototype with AI-assisted implementation; no live operational data or claimed business savings.