A Multi-Stop Optimized Truck Load Logistics Solution for the Pharmaceutical Industry
This paper presents a real-life example of a pharmaceutical company’s logistics problem. The company has two distribution centers, to serve multiple customers across the United States. The aim of this paper is to develop a multi-stop optimized truck load solution to reduce costs and optimize logistics. The solution consists of utilizing DBSCAN - Density Based Spatial Clustering of Applications with Noise to cluster the various customer locations for multi-stops of trucks, then using a combination of a heuristic algorithm and dynamic optimization to create optimized delivery schedules and optimized truck loads, and finally using an algorithm to calculate the logistics costs as per the rate matrix of the carrier. Keywords – clustering, DBSCAN, dynamic optimization, heuristic algorithm, logistics. Advisor - Dr. Robert Voigt, Dr. Vittaldas Prabhu. Reader - Dr. Suvrat Dhanorkar
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|A Multi-Stop Optimized Truck Load Logistics Solution for the Pharmaceutical Industry
|All rights reserved
|July 04, 2020
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