Hospital admission planning plays an important role for managing and allocating hospital resources by emphasizing on an optimal use of operating theater time. The objective of this work is to develop a mixed integer linear programming model in order to minimize the total absolute deviations of the operating room resource utilizations from their target utilizations for the multiple-day planning horizon. The stochastic resource requirements such as length of stay, emergency arrivals, and unattended patients (no-shows) are considered in the proposed formulation. The mathematical model was tested with a sample data set. Results show that the deviations from the target resource utilizations are decreased by 0%, 3.18%, 0.45%, and 3.00% for each type of hospital resources; namely, operating theater time, intensive-care beds, intensive-care nursing staff and medium-care beds, respectively. Moreover, the gap deviated from the overall target resource utilization is improved by 1%.Keywords -Hospital admission planning, mixed integer linear programming, emergency admission, no-shows 978-1-4577-0739-1/11/$26.00 ©2011 IEEE

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This paper studies collaborative capacity sharing between two liner shipping companies by investigating the impacts of collaboration on the sharing of fuel-consumption. The proposed model is extended from the vehicle routing problem with time windows (VRPTW) through the inclusion of slow-steaming decision variables and constraints to manage the sharing of fuel consumption. Two cases differing in size are developed using Indonesian archipelago for the data background and three policies on fuel-consumption sharing are investigated: open policy, proportionate-sharing policy, and equal-sharing policy. The application of the collaborative model in Indonesian archipelago contributes to the scant literature in maritime logistics collaboration. The optimisation results from generated instances show that the open policy leads to minimum total fuel consumption but the unclear pattern in fuel-consumption sharing between carriers makes it impractical for planning purposes. Moreover, the fuel consumptions of the proportionate-sharing and equal-sharing policies are not significantly different but the smaller variance in the results of the proportionate-sharing policy indicates more predictability. The proportionate-sharing policy is therefore considered the most suitable for route planning.

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This paper proposes a multi-objective evolutionary algorithm in maritime logistics collaboration of two liner shipping companies in joint-routing network design. The model is called the ship routing problem and two objectives being minimised are total cost and deviation in fair cost proportion. The method combines NSGA-II and the principles of effective genetic algorithms from the literature, and an example of application with data background from the Indonesian archipelago is demonstrated. Both the method and its application in real-life problems have never been encountered in academic publication, therefore this research has significant contribution and practical values on those fronts. Three dispersal mechanisms are tested with two different mutation probabilities and the results suggest that different rate supports different mechanism. Running times are longer in higher mutation rate, but in general the DV(1) mechanism is faster than both DL mechanisms. Non-dominated solutions are found and translated to joint routings of both carriers.