loading and routing logistics
Routing for multiple trucks optimized for number of deliveries, weight and volume.
This use case demonstrates how globalMOO optimizes the multiple objectives of multiple trucks. Objectives include balancing loads for truck weight and volume and number of deliveries per truck.

Streamlining Delivery logistics balancing multiple objectives
globalMOO is turning complex issues into actionable, optimized strategies addressing parcel optimization for multiple trucks, multi type vehicle parcel optimization, multi type vehicle, multi type parcel and routing optimization.
Problem Description:
Input Variables:
- 100 packages with different weights and volumes going to different addresses in Denver, CO
Objectives:
- All packages should be delivered using 4 or 5 or 6 trucks.
- Weight of each truck should be balanced with each other (dependent on the number of trucks.)
- Volume of each truck should be balanced to each other (dependent on the number of trucks.)
- Number of deliveries should be balanced among the trucks (dependent on the number of trucks.)
Watch the following 1 minute video to decipher the power of globalMOO on solving a multi-objective routing problem
globalMOO Outperforms Competing Algorithms
In benchmark evaluations, globalMOO finds optimal routes faster than competing algorithms, while discovering solutions that balance far more disparate variables and business needs than are usually considered. The figure shows run time comparison of globalMOO with Google’s routing algorithm as a function of number of deliveries. The run time of globalMOO is not dependent on the number of deliveries while Google routing algorithm run times increase exponentially as a function of the number of deliveries. For 1,000 deliveries globalMOO can find an optimal route 10,000 faster than the Google routing algorithm.

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