there is a need to analyze and map rainfall erosivity to assess soil erosion at the regional scale. the objectives of this study were to develop a regional model to estimate seasonal erosivity from seasonal rainfall data and to study temporal and spatial distribution of rainfall erosivity for the gorganrood drainage basin in the northeast of iran. six gauging stations with a high temporal resol...

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, rand...

The neural network learning process is a sequence of network updates and can be represented b y sequence of points in the weight space that we call a learning trajectory. In this paper a new learning approach based on repetitive bounded depth trajectory branching M proposed. This approach has objectives of improving generalization and speeding up Convergence b y avoiding local minima when selec...

This paper proposes a fast and simple unsupervised word segmentation algorithm that utilizes the local predictability of adjacent character sequences, while searching for a leasteffort representation of the data. The model uses branching entropy as a means of constraining the hypothesis space, in order to efficiently obtain a solution that minimizes the length of a two-part MDL code. An evaluat...

We present a method for modelling and estimating branching structures, such as blood vessel bifurcations, from medical images. Branches are modelled as a superposition of Gaussian functions in a local region which describe the amplitude, position and orientations of intersecting linear features. The centroids of component features are separated by applying K-means to the local Fourier phase and...

L-systems are widely used in the modelling of branching structures and the growth of biological objects such as plants, nerves and the airways in lungs. The derivation of such L-system models involves a lot of hard mental work and time-consuming manual procedures. A method based on genetic algorithms for automating the derivation of L-systems is presented here. The method involves representatio...

Finding a feasible solution to a generic Mixed-Integer Program (MIP) is often a very difficult task. Recently, two heuristic approaches called Feasibility Pump and Local Branching have been proposed to address the problem of finding a feasible solution and improving it, respectively. In this paper we introduce and analyze computationally a hybrid algorithm that uses the feasibility pump method ...

Walter Rei, Michel Gendreau Département d’informatique et de recherche opérationnelle and Centre de recherche sur les transports, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Canada, H3C 3J7, {[email protected], [email protected]} Jean-François Cordeau, Patrick Soriano HEC and Centre de recherche sur les transports, Montréal, 3000 chemin de la Côte-Sainte-C...

In this paper we develop a variable neighborhood search (VNS) heuristic for solving mixed-integer programs (MIPs). It uses CPLEX, the general-purpose MIP solver, as a black-box. Neighborhoods around the incumbent solution are defined by adding constraints to the original problem, as suggested in the recent local branching (LB) method of Fischetti and Lodi (Mathematical Programming Series B 2003...

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...