Search results for "algorithm"
showing 10 items of 4887 documents
JASP: a program to estimate discovery and exclusion limits in prospective studies of searches
1997
Abstract This program computes the discovery and exclusion limits that can be set in prospective studies of new experiments in the search for new phenomena. It properly takes into account the different outcomes that the experiment can obtain including the possible signal and background fluctuations. The procedure gives in general more conservative limits than those obtained assuming that the experiment will obtain a number of events equal to the expected mean. The difference may be essential in those cases where only one experiment is foreseen to be carried out.
Identification of parameters of dynamic Preisach model by neural networks
2008
In this paper, an approach that allows to identify the parameters of dynamic Preisach model is presented. The fundamental idea of this method is to identify the parameters of a material by using a neural network trained by a collection of hysteresis curves, whose Preisach model is known. After a brief description of dynamic Preisach Model, the neural network that has been used is introduced. The construction of the training data set is illustrated. Finally, the effectiveness of the method is tested on both numerical as well as experimental data.
A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling
2009
We consider the problem of allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. More specifically, the user is presented with `n ' sets of data points, S 1 , S 2 , ..., S n , where the set S i has N i points drawn from two classes {*** 1 , *** 2 }. A random sample in set S i belongs to *** 1 with probability u i and to *** 2 with probability 1 *** u i , with {u i }. i = 1, 2, ...n , being the quantities to be learnt. The problem is both interesting and non-trivial because while both n and each N i are large, the number of samples that can be drawn is bounded by a constant, c . We solve the problem by first modelling it a…
A Maximal-Space Algorithm for the Container Loading Problem
2008
In this paper, a greedy randomized adaptive search procedure (GRASP) for the container loading problem is presented. This approach is based on a constructive block heuristic that builds upon the concept of maximal space, a nondisjoint representation of the free space in a container. This new algorithm is extensively tested over the complete set of Bischoff and Ratcliff problems [Bischoff, E. E., M. S. W. Ratcliff. 1995. Issues in the development of approaches to container loading. Omega 23 377–390], ranging from weakly heterogeneous to strongly heterogeneous cargo, and outperforms all the known nonparallel approaches that, partially or completely, have used this set of test problems. When …
A Scatter Search Algorithm for the Split Delivery Vehicle Routing Problem
2008
In this chapter we present a metaheuristic procedure constructed for the special case of the Vehicle Routing Problem in which the demands of clients can be split, i.e., any client can be serviced by more than one vehicle. The proposed algorithm, based on the scatter search methodology, produces a feasible solution using the minimum number of vehicles. The quality of the obtained results is comparable to the best results known up to date on a set of instances previously published in the literature.
Efficient Local Search Limitation Strategies for Vehicle Routing Problems
2008
In this paper we examine five different strategies for limiting the local search neighborhoods in the context of vehicle routing problems. The vehicle routing problem deals with the assignment of a set of transportation orders to a fleet of vehicles, and the sequencing of stops for each vehicle to minimize transportation costs. The examined strategies are applied to three standard neighborhoods and implemented in a recently suggested powerful memetic algorithm. Experimental results on 26 well-known benchmark problems indicate significant speedups of almost 80% without worsening the solution quality. On the contrary, in 12 cases new best solutions were obtained.
Testing Independence: A New Approach
2000
In time series analysis and modelling, testing for independence allows us to determine if the estimated model is correctly specified. In this work, we present a very simple method to test for serial independence, based on the two-dimensional embedding vectors (the so-called “2-histories”), and we analyse the power and size of such a procedure against a wide set of linear and nonlinear alternatives.
Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective optimization, UPS-EMOA
2010
Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.
Left-to-right tree pattern matching
1991
We propose a new technique to construct left-to-right matching automata for trees. Our method is based on the novel concept of prefix unifcation which is used to compute a certain closure of the pattern set. From the closure a kind of deterministic matching automaton can be derived immediately. We also point out how to perform the construction incrementally which makes our approach suitable for applications in which pattern sets change dynamically, such as in the Knuth-Bendix completion algorithm.
<strong>New tool useful for drug discovery validated through benchmark datasets</strong>
2018
Atomic Weighted Vectors (AWVs) are vectors that contain the codified information of molecular structures, which can apply to a set of Aggregation Operators (AOs) to calculate total and local molecular descriptors (MDs). This article presents an exploratory study of a new tool useful for drug discovery using different datasets, such as DRAGON and Sutherland’s datasets, as well as their comparison with other well-known approaches. In order to evaluate the performance of the tool, several statistics and QSAR/QSPR experiments were performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by the way of an information theory-based algorithm. …