J
Joseph Wilck
Researcher at College of William & Mary
Publications - 45
Citations - 277
Joseph Wilck is an academic researcher from College of William & Mary. The author has contributed to research in topics: Vehicle routing problem & Routing (electronic design automation). The author has an hindex of 8, co-authored 43 publications receiving 230 citations. Previous affiliations of Joseph Wilck include East Carolina University & United States Air Force Academy.
Papers
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Journal ArticleDOI
A Genetic Algorithm for the Split Delivery Vehicle Routing Problem
Joseph Wilck,Tom M. Cavalier +1 more
TL;DR: Two hybrid genetic algorithms are developed for the Split Delivery Vehicle Routing Problem and computational results are given for thirty-two data sets from previous literature.
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A Construction Heuristic for the Split Delivery Vehicle Routing Problem
Joseph Wilck,Tom M. Cavalier +1 more
TL;DR: In this paper, a new construction heuristic is developed for the split delivery vehicle routing problem (SDVRP) and computational results are given for thirty-two data sets from previous literature.
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Chasing John Snow: data analytics in the COVID-19 era
TL;DR: The actions taken by countries around the world are analyzed and it is shown that when governments employ strict measures early, particularly those that enforce social distancing and include widespread testing and comprehensive contact tracing, they are more likely to experience better outcomes.
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Challenges and opportunities to integrate the oldest and newest manufacturing processes: metal casting and additive manufacturing
TL;DR: The current state, technological challenges, economic opportunities and future directions in the growing “indirect” hybrid manufacturing ecosystem, which integrates traditional metal casting with the production of tooling via additive manufacturing (AM) process including three-dimensional sand printing (3DSP) and printed wax patterns are investigated.
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An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem
TL;DR: Two approaches using, 1) Ant Colony Optimization and 2) hybrid metaheuristics algorithm comprising a combination of ACO, Genetic Algorithm and heuristics are proposed and tested on benchmark SDVRP problems and indicate that the two proposed algorithms are competitive in both solution quality and solution time.