Recent radar research interests in the Pareto distribution as a model for X-band maritime surveillance radar clutter returns have resulted in analysis of the asymptotic behaviour of this clutter model. In particular, it is of interest to understand when the Pareto distribution is well approximated by an Exponential distribution. The justification for this is that under the latter clutter model ...

We consider Pareto analysis of reachable states of multi-priced timed automata (MPTA): timed automata equipped with multiple observers that keep track of costs (to be minimised) and rewards (to be maximised) along a computation. Each observer has a constant non-negative derivative which may depend on the location of the MPTA. We study the Pareto Domination Problem, which asks whether it is poss...

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting par...

Welfare economics typically holds that market outcomes are Pareto efficient only if markets are competitive and average costs are constant or increasing. Otherwise, to attain market efficiency requires some regulatory implementation of a rule to equate price to marginal cost, though the ability of such a pricing rule to accomplish this is tempered by second-best considerations. In contrast to t...

In this investigation, the multi-objective selection and optimization of a gantry machine tool is achieved by analytic hierarchy process, multi-objective genetic algorithm, and Pareto-Edgeworth-Grierson–multi-criteria decision-making method. The objectives include maximum static deformation, the first four natural frequencies, mass, and fabrication cost of the gantry. Further structural optimiz...

Many real-world problems show both multiobjective as well as dynamic characteristics. In order to use multiobjective evolutionary optimization algorithms (MOEA) efficiently, a systematic analysis of the behavior of these algorithms in dynamic environments is necessary. Dynamic fitness functions can be classified into problems with moving Pareto fronts and Pareto sets having varying speed, shape...

This paper discusses Pareto efficient allocations of an environmental commodity, which is both a public good and a public bad, with an application to the Scandinavian problem of conserving wild predators that are killing semi-domesticated reindeer. The paper begins by briefly outlining this conflict. This is followed by a theoretical analysis employing a diagrammatic tool called the Kolm triang...