in this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the p-mmrcpsp while due dates are included i...

We introduce a class of “inverse parametric optimization” problems, in which one is given both a parametric optimization problem and a desired optimal solution; the task is to determine parameter values that lead to the given solution. We describe algorithms for solving such problems for minimum spanning trees, shortest paths, and other “optimal subgraph” problems, and discuss applications in m...

Variable selection is an important task in machine learning and data mining applications. In many real world problems a huge volume of data is often available which corresponds to a large number of variables. When developing a model for classification, clustering or other applications, the search of an optimal subset of relevant input variables is crucial. In this paper an automatic variable se...

genetic trend for production traits were estimated in iranian holstein cattle using the first lactation data recorded by cattle breeding and dairy product improvement center of the state from 1991 to 2006. effect of some factors on genetic trend was investigated using data from 18 large herds. (co) variance components and genetic parameters were estimated, using five trait animal model and em-a...

Gene expression programming has been shown to be an important algorithm in the optimisation of complex systems. However, it has many more operators and parameters than standard genetic programming, each of which needs to be set when applying the algorithm to new problems. In this paper, an adaptive approach for setting probabilities for genetic operators in gene expression programming (GEP) usi...

In this study, two goals are followed. First, by means of the Generalized Differential Quadrature (GDQ) method, parametric analysis on the vibration characteristics of three-parameter Functionally Graded (FG) beams on variable elastic foundations is studied. These parameters include (a) three parameters of power-law distribution, (b) variable Winkler foundation modulus, (c) two-parameter elasti...

logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. transportation network design is then one of the most important fields of logistic network. this study is concerned with designing a multi-stage and multi-product logistic network. at first, a mixed integer nonlinear programming model...

in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...

The analysis of viral genetic sequence data collected during disease outbreaks has emerged as a promising new tool for understanding infectious disease dynamics and designing control measures against infectious diseases. Hence, there is a need for statistical methodologies that effectively integrate genetic data with other epidemiological data to perform inference on the underlying disease dyna...