Standard decision rules in CEA are founded on a single objective to maximise health subject to a single and exogenous budget constraint.  In essence, this is a well-specified constrained optimisation problem.  The difficulty of using mathematical programming (MP) solutions to inform the allocation problem is that the informational demands are not feasible.  However, it does provide an opportunity to evaluate the performance of simple ex-ante decision rules that have been proposed, some of which are being used to make decisions about healthcare technologies.  Different decision rules are evaluated which compare: 1) the health gained and forgone for a new technology based on an estimate of the cost-effectiveness threshold, and 2) the health effects of the new technology with the health effects of those technologies which must be displaced to accommodate its additional costs.  The performance of each is evaluated through a simulation exercise, which using shopping at the supermarket as an analogy to the health care system.  An initial basket of goods represents the initial allocation and specifies the budget constraint.  The task is to improve the contents of the basket by examining other things on the shelves and applying one of the decision rules.  Performance is measured by: 1) how close each can get to the optimal basket (a MP solution), and 2) how quickly each improves the initial basket.  We explore when each decision rule performs at its best and when one is likely to outperform the other.  This includes: indivisibly of technologies and programmes, size of the budget relative to programme costs, the efficiency of exiting technologies; the type of information available to decision makers and whether they are able to learn from examining more products.  This helps to identify where additional information (e.g., a better estimate of the threshold) might be most valuable.