For tutorial, real-time logistics, and math applications...
👋 Welcome! Here is how to play with this simulator:
• Step 1: Enter Route Details to query Live OSRM Traffic API and real-time Open-Meteo weather forecasting.
• Step 2: Check Daily Controls to adjust evaporation parameters, departure time, or truck counts.
• Step 3: The engine calculates net fuel evaporation based on traffic congestion, route temperature, and travel time.
• Step 4: Click ⚡ Auto-Calculate to compute mathematically optimal dispatch schedules.
Your final net profit mathematically subtracts transport hire expenses and the value penalty of evaporated fuel from top-line sales revenues.
Decay rate multiplied by ambient temperature offset above 20°C and total travel duration (hours in transit).
Stock balance must strictly remain between safety stock and maximum tank capacity.
Environmental impact per trip is modeled via diesel combustion metrics ($2.68\text{ kg CO}_2/\text{L}$) plus traffic congestion factor ($\tau_{\text{cong}}$).
Target: over 99.5%
Traffic should stay under 100%
Est. Days of Supply
Sovereign Industrial Intelligence
EJIRO INIJE (PROFESSOR IN PRACTICE)
PAGE 4Predict. Plan. Optimize. Profit.
ABI Engine simulates your entire depot operations for 30 days using live OSRM traffic routing, real weather forecasts, truck performance, and evaporation loss.
Optimal dispatch and OSRM traffic routing increase profit yield by 18.6%.
Evaporation loss minimized by weather-aware departure scheduling.
Best performance recorded during off-peak morning & night travel windows.
Traffic congestion delays and high heat remain the main cost drivers.
Right Stock. Right Time. Maximum Profit.
ABI Engine uses mathematical Economic Order Quantity (EOQ) models and live demand forecasting to reduce stockouts, lower holding costs, and maximize capital flow.
ABI Engine utilizes the **Economic Order Quantity (EOQ)** formula to calculate minimum logistics ordering costs ($S$) and holding losses ($H$):
Green Logistics. Low Carbon. High Reliability.
Page 6 models environmental sustainability (Scope 1 fleet $CO_2$ footprint), diesel fleet wear-and-tear degradation, and Monte Carlo risk probability curves for transit disruptions.