An optimal takeout supply system of intelligent self-pickup cabinets: evidence from dining service during COVID-19.

In order to reduce cross-infections during epidemics such as COVID-19, it is valuable to design a campus takeout system of intelligent self-pickup cabinets (ISPCs). This research aims to design such a system by optimizing the sites of cabinets, their capacity types, and the location–allocation scheme. In view of maximizing profits of the system, we formulate this design problem as a zero–one integer nonlinear programming model, where the demand of takeout is distance dependent and congestion dependent, rather than a fixed constant. On the basis of model property analysis, the original model is transformed into an integer linear programming problem such that it is solved by off-the-shelf solvers. By case study and sensitivity analyses, it is found that: The proposed method is valuable for providing an optimal strategy for a takeout system of ISPCs by optimizing the sites of the cabinets, the capacity types and the location–allocation strategy; With the optimal strategy derived from the proposed model and algorithm, the developed system is more applicable in the areas of intensively distributed users or the areas closer to canteens in view of creating significant effects of scale economy; For the groups of consumers with different distance-dependent or congestion-dependent sensitivities, it is suggested to implement distinct optimal strategies of building the takeout system even for those in the same service area; The takeout demand grows up with an increasing unit selling price in the developed system, rather than reduction as in an ordinary relation between the demand of products and the price. Thus, the designed self-pickup takeout system seems more applicable to be adopted for the high-quality takeout. [ABSTRACT FROM AUTHOR]