Today competitive environment has enforced practitioners and researchers to pay great attention to issues enhancing both production and marketing competitiveness. To do so, it has been obligatory for the firms to consider production side activities while customer requirements are on the other side of competition. In this regard, hybrid make-to-stock (MTS)/make-to-order (MTO) production systems ...

this research deals with axial and oblique impact crash tests on simple and hybrid composite tubes. axial and oblique impact tests have been generated on simple and hybrid composite tubes with one, two and three layers. a drop test rig was used to conduct the experiments. furthermore, in order to gain more detailed knowledge about the crash process, finite element simulations of the experiments...

Although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the problem of scheduling no-idle hybrid flow shops. A mixed integer linear programming model is first developed to mathematically form...

Scheduling problems play a big role in manufacturing and planning the production for increasing the production efficiency and assigning the resources to operations. Furthermore, in many manufacturing systems there is a physical space between stages that called intermediate buffers. In this study, a model is proposed for minimizing the makespan of a hybrid flow shop scheduling problem with inter...

Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...

time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. forecasting accuracy is one of the most important features of forecasting models. nowadays, despite the numerous time series forecasting models which have been proposed in several past decades, it is widely recognized that financial markets are extremely difficult to ...

in this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the shabestar plain, iran. after initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (ga-bp) should be able to reproduce groundwater ...

in a large scale cyclic storage system ,as the number of rule parameters and/or number of operating period increase, general purpose gradient-based nlp solvers and/or genetic algorithms may loose their merits in finding optimally feasible solution to the problem. in these cases hybrid ga which decomposes the main problem into two manageable sub-problems with an iterative scheme between ga and l...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...