In this paper we present a novel transshipment problem for a large apparel retailer that operates an extensive retail network. Our problem is inspired by the logistics operations of a very large fast fashion retailer in Turkey, LC Waikiki, with over 450 retail branches and thousands of products. The purpose of transshipments is to rebalance stocks across the retail network to better match supply with demand. We formulate this problem as a large mixed integer linear program and develop a Lagrangian relaxation with a primal-dual approach to find upper bounds and a simulated annealing based metaheuristic to find promising solutions, both of which have proven to be quite effective.While our metaheuristic does not always produce better solutions than a commercial optimizer, it has consistently produced solutions with optimality gaps lower than 7% while the commercial optimizer may produce very poor solutions with optimality gaps as high as almost 300%. We have also conducted a set of numerical experiments to uncover implications of various operational practices of LC Waikiki on its system's performance and important managerial insights.

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This document is the Accepted Manuscript version of the following article: Soheil Davari, Kemal Kilic, and Siamak Naderi, ???A heuristic approach to solve the preventive health care problem with budget and congestion constraints???, Applied Mathematics and Computation, Vol. 276, pp. 442-453, March 2016. ?? 2016. Under embargo. Embargo end date: 14 January 2018. The Version of Record is available online at doi: https://doi.org/10.1016/j.amc.2015.11.073.Preventive health care is of utmost importance to governments since they can make massive savings on health care expenditure and promote the well-being of the society. Preventive care includes many services such as cancer screenings, vaccinations, hepatitis screenings, and smoking cessation programs. Despite the benefits of these services, their uptake is not satisfactory in many countries in the world. This can be attributed to financial barriers, social issues., and other factors. One of the most important barriers for preventive care is accessibility to proper services, which is a function of various qualitative and quantitative factors such as the distance to travel, waiting time, vicinity of facilities to other attractive facilities (such as shopping malls), and even the cleanliness of the facilities. Statistics show that even a small improvement in people???s participation can save massive amounts of money for any government and improve the well-being of the people in a society. This paper addresses the problem of designing a preventive health care network considering impatient clients, and budget constraints. The objective is to maximize the accessibility of services to people. We model the problem as a mixed-integer programming problem with budget constraints, and congestion considerations. An efficient variable neighborhood search procedure is proposed and computational experiments are performed on a large set of instances

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