this paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. portfolio optimization problem is a quadratic programming model and, changes to np-hard if the number of assets and constraints has increased, and it cannot be solved using common mathematical methods in a reasonable time. therefore, a heuristic or meta-heuristic algorithm should b...

Area exploration in robotics is done by number of methods some of which select next target based on shortest distance, other uses utility function and the most frequently used method is through frontier based area exploration which is boundary between explored and unexplored cells. In view of Multi robot, extra care should be taken as it may possible that two robot may collide or explore alread...

Tree pattern matching (tpm) algorithms play an important role in practical applications such as compilers and XML document validation. Many tpm algorithms based on tree automata have appeared in the literature. For reasons of efficiency, these automata are preferably deterministic. Deterministic root-to-frontier tree automata (drftas) are less powerful than nondeterministic ones, and no root-to...

Abstra t. Tree pattern mat hing (tpm) algorithms play an important role in pra ti al appli ations su h as ompilers and XML do ument validation. Many tpm algorithms based on tree automata have appeared in the literature. For reasons of eÆ ien y, these automata are preferably deterministi . Deterministi root-to-frontier tree automata (drftas) are less powerful than nondeterministi ones, and no ro...

Knowledge frontier discovery is a novel technique for identifying interesting subpopulations of a dataset with respect to classification performance. A knowledge frontier is a collection of meaningful groups where any sub-partition with significantly different predictive accuracy is not meaningful. This research introduces knowledge frontiers and knowledge frontier discovery. The first knowledg...

There arises situations where an autonomous robot needs to navigate to a target location and no information is available about the terrain. Frontier based navigation is one of the most efficient methods of exploration and navigation for such situations. In a frontier based strategy, the robot navigates to the target location by detecting intermediate frontier regions, which are points lying on ...

This paper studies an infinite-horizon adverse selection model with an underlying Markov information process and a risk-neutral agent. It introduces a graphic representation of continuation contracts and continuation-payoff frontiers, namely finite policy graphs, and provides an algorithm that generates a sequence of such graphs to approximate the optimal policy graph. The algorithm performs an...

The paper analyzes the extension of frontier search to the multiobjective framework. A frontier multiobjective A* search algorithm is developed, some formal properties are presented, and its performance is compared to those of other multiobjective search algorithms. The new algorithm is adequate for both monotone and non-monotone heuristics.

The most important issue in multi-objective optimization problems is to determine the Pareto points along the Pareto frontier. If the optimization problem involves multiple conflicting objectives, the results obtained from the Pareto-optimality will have the trade-off solutions that shaping the Pareto frontier. Each of these solutions lies at the boundary of the Pareto frontier, such that the i...