Abstract
This paper investigates the development and application of a general meta-heuristic, Meta-RaPS (meta-heuristic for randomized priority search), to the traveling salesman problem (TSP). The Meta-RaPS approach is tested on several established test sets. The Meta-RaPS approach outperformed most other solution methodologies in terms of percent difference from optimal. Additionally, an industry case study that incorporates Meta-RaPS TSP in a large truck route assignment model is presented. The company estimates a more than 50% reduction in engineering time and over $2.5 million annual savings in transportation costs using the automated Meta-RaPS TSP tool compared to their current method.
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