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AbstractPurpose -The purpose of this paper is to describe the development and teaching of graduate courses providing in-depth experiential learning employing commercial supply chain management software. The benefits of teaching such courses are described, the challenges in offering such courses are identified, and some solutions to overcome the challenges are offered. Design/methodology/approach -The experiences of the authors in developing and teaching supply chain management courses utilizing commercial software provided a basis for discussing the benefits and challenges associated with teaching students the management of modern supply chains using commercial decision-support software. Findings -Incorporating commercial software in university programs presents a myriad of challenges and therefore is rarely done. However, providing students with in-depth knowledge of commercial logistics and supply chain management software improves their understanding of supply chain issues and provides a key differentiator in the marketplace. Modeling real-world supply chains using commercial software enhances student's education by providing relevant experiential exposure to real-world problems and decision-support tools. Originality/value -The observations of the authors in developing and teaching courses in supply chain management utilizing commercial software afford a unique viewpoint and roadmap for others regarding teaching supply chain management in academic environments.
This paper describes the development of tools to support better scheduling and sequencing of barge tows on a congested portion of the Upper Mississippi River. Our study section covers 100 miles and includes five 600-foot long locks that handle commercial tows up to 1200 feet long. Due to the varying nature of the traffic and lockage times (especially the need to split long tows to pass through smaller locks), long queues may form at the locks. This paper provides an overview of our research, including evaluation of lock and traffic management policies, development of a detailed multi-lock simulation model, evaluation of decision rules for sequencing vessels in queues, and development of a prototype GIS-based vessel tracking system. Our findings suggest that better sequencing of vessels at locks would provide small improvements at current traffic levels, but may reduce waiting time by as much as 25% with increasing levels of demand.
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