Order optimization : a comparative analysis of heuristics and machine learning

Order optimization includes many variables related to inventory management and transportation management. In this thesis, we present a solution approach that optimizes transportation path selection based on an inventory management system and transportation network. The objective of the approach is to minimize costs and emissions while minimizing potential risks. The solution compares a simple heuristic, a complex heuristic, and a learning heuristic to compare the performance. A Pareto frontier of solutions is presented on costs and emissions.