the objective followed in this study was to compare six software packages (dfreml, wombat, asreml, matvec, dmu and thrgibbsf90) as based on some such features as being user friendly, easing computational facilities as well as accuracy and precision of the estimated genetic vs. environmental parameters. for conduction of the study, simulated and field data (birth weights and weaning weight of ba...

data related to holstein dairy cattle from 1987 to 2004 were obtained from animal breeding center of iran to estimate the genetic and phenotypic trends. variance components and genetic parameters of the first lactation records were estimated using restricted maximum likelihood method and aireml algorithm through matvec program. animal breeding values were predicted through multiple-trait animal...

BP neural network can approximate nonlinear functions in any degree of accuracy. However, it exhibits the shortcoming of slow convergence, and it is easy to fall into local minimum value. The genetic algorithm has academic advantages both at home and abroad. On the basis of analysis on features of genetic algorithm and BP neural network, the explanations on the necessity of combining genetic al...

Customer service level is of prime importance in today competitive world and has various dimensions with delivery quality being one of the most important ones. Delivery quality has several parameters such as deliver time window options, time window size, etc. In this paper we focus on one of these parameters, namely time window setting. It has a direct impact upon customer satisfaction and busi...

The process of identifying the optimal parameters for an optimization algorithm or a machine learning one is a costly combinatorial problem because it involves the search of a large, possibly infinite, space of candidate parameter sets. Our work compares grid search with a simple genetic algorithm when used to find the optimal parameter setting for an ID3 like learner operating on given dataset...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...

Damage detection has been focused by researchers because of its importance in engineering practices. Therefore, different approaches have been presented to detect damage location in structures. However, the higher the accuracy of methods is required the more complex deliberations. Based on the conventional studies, it was observed that the damage locations and its size are associated with dynam...

Nowadays, Electrical Discharge Machining (EDM) has become one of the most extensively used non-traditional material removal process. Its unique feature of using thermal energy to machine hard to machine electrically conductive materials is its distinctive advantage in the manufacturing of moulds, dies and aerospace components. Howevere, EDM is a costly process and hence proper selection of its ...

in this study, a bi-objective model for integrated planning of production-distribution in a multi-level supply chain network with multiple product types and multi time periods is presented. the supply chain network including manufacturers, distribution centers, retailers and final customers is proposed. the proposed model minimizes the total supply chain costs and transforming time of products ...

Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...