modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. in order to obtain the maximum amount of yeast (saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. to determine substrate feeding in a fed-batch bioreactor, a simulated annealing (sa) approach was examine...

Sustainability in agricultural is determined by aspects like economy, society and environment. Multi-objective programming (MOP) model has been a widely used tool for studying and analyzing the sustainability of agricultural system. However, optimization models in most applications are forced to use data which is uncertain. Recently, robust optimization has been used as an optimization model th...

in this research work, a novel parallel manipulator with high positioning and orienting rate is introduced. this mechanism has two rotational and one translational degree of freedom. kinematics and jacobian analysis are investigated. moreover, workspace analysis and optimization has been performed by using genetic algorithm toolbox in matlab software. because of decreasing moving elements, it i...

Many portfolio optimization problems deal with allocation of assets which carry a relatively high market price. Therefore, it is necessary to determine the integer value of assets when we deal with portfolio optimization. In addition, one of the main concerns with most portfolio optimization is associated with the type of constraints considered in different models. In many cases, the resulted p...

The radius of robust feasibility provides a numerical value for the largest possible uncertainty set that guarantees counterpart mathematical program with uncertain constraints. objective this review state-of-the-art in field is to present useful tool optimization its potential users and avoid undesirable overlapping research works on topic as those we have recently detected. In paper overview ...

We propose a distributionally robust optimization formulation with Wasserstein-based uncertainty set for selecting grouped variables under perturbations on the data both linear regression and classification problems. The resulting model offers robustness explanations least absolute shrinkage selection operator algorithms highlights connection between regularization. prove probabilistic bounds o...