Afghan-Australians: Diasporic Tensions,Homeland Transformations and the “2014 Syndrome”

With the withdrawal of NATO-led troops from Afghanistan pending in 2014, Afghanistan and its sizeable diaspora are facing an ambiguous new beginning. As in Afghanistan itself, the 35,000-strong Afghan community in Australia is negotiating what has been labelled the “2014 Syndrome”—a chronic state of anxiety about Afghanistan's future. Drawing on data from a series of dialogues and consultations held with Afghan-Australians of different ethnicities in Melbourne in 2012 and 2013, this article contextualizes and critically examines the tensions and shared concerns of the Afghan-Australian community in light of the impending withdrawal. Our study shows that the 2014 Syndrome has exacerbated existing tensions over “Afghan” identity in Australia, which has become intertwined with tensions over the status of Hazara asylum seekers and refugees arriving in Australia. Given the widely held belief amongst Afghan-Australians that the 2014 withdrawal will prompt increased flows of asylum seekers from Afghanistan to Australia, this study argues that tensions around identity frame quite different hopes for the future of Afghanistan and the future of the Afghan-Australian community after 2014.     

Using partially observed Markov processes to select optimal termination time of TV shows

This paper presents a method for optimal control of a running television show. The problem is formulated as a partially observed Markov decision process (POMDP). A show can be in a “good” state, i.e., it should be continued, or it can be in a “bad” state and therefore it should be changed. The ratings of a show are modeled as a stochastic process that depends on the show's state. An optimal rule for a continue/change decision, which maximizes the expected present value of profits from selling advertising time, is expressed in terms of the prior probability of the show being in the good state. The optimal rule depends on the size of the investment in changing a show, the difference in revenues between a “good” and a “bad” show and the number of time periods remaining until the end of the planning horizon. The application of the method is illustrated with simulated ratings as well as real data.     

An Industrial Ocean-Cargo Shipping Problem

This paper reports the modeling and solution of an industrial ocean-cargo shipping problem. The problem involves the delivery of bulk products from an overseas port to transshipment ports on the Atlantic Coast, and then over land to customers. The decisions made include the number and the size of ships to charter in each time period during the planning horizon, the number and location of transshipment ports to use, and transportation from ports to customers. The complexity of this problem is compounded by the cost structure, which includes fixed charges in both ship charters and port operations. Such a large scale, dynamic, and stochastic problem is reduced to a solvable stationary, deterministic, and cyclical model. The process of modeling the problem and the solution of the resultant mixed integer program are described in detail. Recommendations from this study have been implemented.