Controlling schedule instability in hospital food production: a case of thai public hospital in remote area

The demand for Thai public hospital meals did not come from a patient's choice but was medically designed by a doctor, varying on a daily individual health condi-tion. Other than that, it also varies on individual specific health conditions, e.g., kidney disease or gout, which will create a demand for a special diet called a therapeutic diet. This type of complicated demand is known as non-stationary stochastic demand. A delay in food delivery will impact patient health. At the same time, overproduction will lead to food waste. The difference between planned and actual schedules is called schedule insta-bility and should be minimized. Therefore, this paper proposes a lot-sizing policy for Thai public hospitals to reduce schedule instability that works well in remote areas. This re-mote area context received less attention from researchers compared to hospitals in urban areas. The finding shows unique production planning challenges in four public hospital case studies. A stochastic lot-sizing problem was tested under a user-friendly approach, a mixed integer linear programming, to find an optimal replenishment period and quantity that can minimize the expected total cost of a case study hospital located in a remote area. The solution was satisfactory when tested for its probability of negative closing inventory in each period. The result will benefit hospital practitioners in remote areas by improving their food production planning.