Infectious disease outbreaks have occurred many times in the past decades and are more likely to occur in the future. Recently, B€ uy€ uktahtakin et al. (2018) proposed a new epidemics-logistics model to control the 2014 Ebola outbreak in West Africa. Considering that different diseases have dissimilar diffusion dynamics and can cause different public health emergencies, we modify the proposed model by changing capacity constraint, and then apply it to control the 2009 H1N1 outbreak in China. We formulate the problem to be a mixed-integer non-linear programming model (MINLP) and simultaneously determine when to open the new isolated wards and when to close the unused isolated wards. The test results reveal that our model could provide effective suggestions for controlling the H1N1 outbreak, including the appropriate capacity setting and the minimum budget required with different intervention start times.
Distribution network design affects a firm's operating costs and its customer service level. In this paper, we consider distribution network design for improving the closed-loop logistics in a clothing company. We formulate the problem as a mixed-integer nonlinear programming model with an objective of minimizing the annual operating costs. Our model simultaneously determines the optimal number of regional distribution centers (RDCs), identifies location and relative size for each RDC, allocates each city distribution center to a specific RDC, decides on supply ratio for each contracted plant, and specifies the annual operating costs and service level for the best scenario, as well as other scenarios. Test results show that this marketing initiative at the studied company can effectively reduce its annual operating costs. Although this paper is a specific case study, it provides several managerial insights and modeling references for similar facility location and allocation problems.
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