In this write-up, we extend quicksort to the task of fuzzy sorting of intervals. In many situations the precise value of a quantity is uncertain (e.g., any physical measurement is subject to noise). For such situations we may represent a measurement i as a closed interval [ai, bi], where ai ≤ bi. A fuzzysort is defined as a permutation 〈i1, i2, . . . , in〉 of the intervals such that there exist...

A bi-directional many-sided explanation typed multi-step validation method including its implementation architecture has been proposed to diminish validation loads for busy experts. This paper presents a validation tool based on this method. This tool supports the multi-step, bi-directional validation by experts, KEs (Knowledge Engineers) and computers on the Intra/lnternet environment. Particu...

This note proposes a method, which can be applied to searches and more in general to any cross section measurement, to maximize the analysis sensitivity.

The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

In this paper the Path Dissimilarity Problem is considered. The problem has been previously studied in several contexts, the most popular motivated by the need of selecting routes for transportation of hazardous materials. The aim of this paper is to formally introduce the problem as a bi-objective optimization problem, in which a single solution consists of a set of p different paths, and two ...

The multi-level programming problem is defined as an n-person nonzero-sum game with perfect information in which the players move sequentially. The bi-level linear case is addressed in detail. Solutions are obtained by recasting this problem as a standard mathematical probram and appealing to its implicitly separable structure. The reformulated optimization problem is linear save for a ~ompleme...

This paper develops a bi-directional prediction approach to predict the production parameters and performance of differential fibers based on neural networks and a multi-objective evolutionary algorithm. The proposed method does not require accurate description and calculation for the multiple processes, different modes and complex conditions of fiber production. The bi-directional prediction a...

This paper studies charging scheduling problem of electric vehicles (EVs) in the scale of a microgrid (e.g., a university or town) where a set of charging stations are controlled by a central aggregator. A bi-objective optimization problem is formulated to jointly optimize total charging cost and user convenience. Then, a close-to-optimal online scheduling algorithm is proposed as solution. The...

Several indicator-based evolutionary multiobjective optimization algorithms have been proposed in the literature. The notion of optimal μ-distributions formalizes the optimization goal of such algorithms: find a set of μ solutions that maximizes the underlying indicator among all sets with μ solutions. In particular for the often used hypervolume indicator, optimal μ-distributions have been the...