Latin hypercube designs (LHDs) play an important role when approximating computer simulation models. To obtain good space-filling properties, the maximin criterion is frequently used. Unfortunately, constructing maximin LHDs can be quite time-consuming when the number of dimensions and design points increase. In these cases, we can use approximate maximin LHDs. In this paper, we construct bound...

a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights that are the most advantages for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the same s...

In a partition model, we show that each maximin individually rational and ex-ante maximin efficient allocation of a single good economy is implementable as a maximin equilibrium. When there are more than one good, we introduce three conditions. If none of the three conditions is satisfied, then a maximin individually rational and ex-ante maximin efficient allocation may not be implementable. Ho...

An algorithm to achieve maximal spread and almost perfectly distributed Pareto fronts is presented. The MaxiMin algorithm add points to the archive of selected individuals one by one, each point which is added maximizes the distance from the current selected points. This method is independent of the evolutionary operators used to perform the search. This work explains how to combine the MaxiMin...

This paper studies maximin paths in the context of a standard exhaustible resource model. Under the assumption that the resource is important in production, it establishes the efficiency and uniqueness of non-trivial maximin paths. It uses these results to study the nature of the maximin value and policy functions. The value function is shown to be differentiable with respect to the initial res...

For the binary response model, we determine optimal designs based on the D-optimal criterion which are robust with respect to misspecifications of the unknown parameters. We propose a maximin approach and provide a numerical method to identify the best two point designs for the commonly applied link functions. This method is broadly applicable and can be extended to designs with a given number ...

We introduce the idea of implementation under ambiguity. In particular, we study maximin efficient notions for an ambiguous asymmetric information economy (i.e., economies where agents’ preferences are maximin a la Wald [34]). The interest on the maximin preferences lies in the fact that maximin efficient allocations are always incentive compatible (de CastroYannelis [11]), a result which is fa...

We present a new decision rule, maximin safety, that seeks to maintain a large margin from the worst outcome, in much the same way minimax regret seeks to minimize distance from the best. We argue that maximin safety is valuable both descriptively and normatively. Descriptively, maximin safety explains the well-known decoy effect, in which the introduction of a dominated option changes preferen...

The knowledge-based rational decision model (KBR-model), developed in [1], offers an approach to rational decision making in a non-probabilistic setting, e.g., in perfect information games with deterministic payoffs. The KBR-model is an epistemically explicit form of standard game-theoretical assumptions, e.g., Harsanyi’s Maximin Postulate. This model suggests following maximin strategy over al...