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The transportation sector produces a large portion of greenhouse gas emissions in the United States. Meeting ambitious reductions in greenhouse gasses requires large-scale adoption of battery electric vehicles and has led to several policies and laws aimed at incentivizing their sales. While electric vehicles comprise a small percentage of the overall fleets of vehicles, the expected production of electric vehicles is soon expected to be in the millions. This will create challenges in providing an adequate charging infrastructure, as well as the ensuing management of the overall electricity demand at the grid level. In this work, a novel smart-charging protocol for battery electric vehicle charging at workplace parking structures is proposed. The Octopus Charger-based Mixed Integer Linear Programming protocol allows octopus chargers (i.e., charging stations with multiple cables) to independently schedule charging periods for their assigned vehicles. The proposed protocols can manage a parking structure demand load while reducing the number of installed charging stations. Driving patterns from the National Household Travel Survey were used to perform simulations, to verify and quantify the effectiveness of the proposed protocol. The proposed protocol resulted in improved peak load reductions for all simulated smart-charging scenarios when compared with uncontrolled charging. Critically, the assignment algorithm resulted in a number of required chargers close to the theoretical minimum. [ABSTRACT FROM AUTHOR]