Properties - Myna Delivery Planner

Delivery Time Windows

Breakfast Start Time Time when breakfast deliveries begin (same as dispatch start by default)

Breakfast End Time Time when breakfast deliveries must end

Lunch Start Time Time when lunch deliveries begin (same as dispatch start by default)

Lunch End Time Time when lunch deliveries must end

Dinner Start Time Time when dinner deliveries begin (same as dispatch start by default)

Dinner End Time Time when dinner deliveries must end

Dispatch Windows

Breakfast Dispatch Start Earliest time to dispatch breakfast routes

Breakfast Dispatch End Latest time to dispatch breakfast routes

Lunch Dispatch Start Earliest time to dispatch lunch routes

Lunch Dispatch End Latest time to dispatch lunch routes

Dinner Dispatch Start Earliest time to dispatch dinner routes

Dinner Dispatch End Latest time to dispatch dinner routes

Route Optimization

Note: Max route duration is automatically calculated from delivery time windows above (end time - start time for each meal)

Service Time (minutes) Time spent at each delivery location

Max Orders Per Route Maximum number of orders in a single route

Buffer Orders Extra orders capacity for overloaded routes

Optimization Time Limit (seconds) Maximum time to spend optimizing routes

Max Additional Drivers Extra drivers to use if needed

Vehicle Settings

Default Vehicle Type Default vehicle type for new routes

Bike Max Orders Maximum orders per bike

Motorbike Max Orders Maximum orders per motorbike

Car Max Orders Maximum orders per car

Bike Avg Speed (km/h) Average bike speed for time estimates

Motorbike Avg Speed (km/h) Average motorbike speed for time estimates

Car Avg Speed (km/h) Average car speed for time estimates

Clustering Settings

Enable Clustering Use clustering algorithms for route optimization

Clustering Method Algorithm to use for clustering

Cluster Softness Factor 0 = strict clusters, 1 = ignore clusters

Clustering Method DBSCAN for pure geographic clustering, K-Means for capacity-based

DBSCAN Radius (km) Max distance between points in same cluster (default 2km)

DBSCAN Min Samples Minimum points to form a cluster (default 2)

Auto Determine Clusters Automatically determine number of clusters

Max Clusters Maximum number of clusters if auto mode

Same Location Threshold (km) Distance to consider locations as the same

Payment Settings

Base Pay Per Route Base payment for each route delivered (in rupees)

2 Meals Incentive Additional incentive when driver delivers 2 meals in a day (split among routes)

3 Meals Incentive Additional incentive when driver delivers 3 meals in a day (split among routes)

Per Kilometer Rate Payment per kilometer (includes return distance to depot)

💡 Payment Logic: Total Pay = Base Pay + (Incentive ÷ Number of Routes) + (Per KM Rate × Total Distance)

Example 1: Driver with 2 meals/day, 25km and 30km routes:
Route 1: ₹200 + (₹100 ÷ 2) + (₹4 × 25) = ₹350 | Route 2: ₹200 + (₹100 ÷ 2) + (₹4 × 30) = ₹370
Total base for driver: 200×2 + 100 = ₹500

Example 2: Driver with 3 meals/day (30km each route):
Each route: ₹200 + (₹150 ÷ 3) + (₹4 × 30) = ₹200 + ₹50 + ₹120 = ₹370
Total base for driver: 200×3 + 150 = ₹750

Performance Tuning

Multi-Start Optimization Use multiple random starts for better solutions

Small Problem Starts (≤10 orders) Number of random starts for small problems

Medium Problem Starts (11-20 orders) Number of random starts for medium problems

Large Problem Starts (21+ orders) Number of random starts for large problems

Simulated Annealing Iterations Max iterations for simulated annealing

Lin-Kernighan Iterations Max iterations for Lin-Kernighan heuristic