Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. Howeve...

We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as contextual bandits, encompasses a wide variety of applications including health-care policy and Internet advertising. A central task is evaluation of a new policy given historic data consisting of contexts, actions an...

an optimal desirability function method is proposed to optimize multiple responses in multiple production scenarios, simultaneously. in dynamic environments, changes in production requirements in each condition create different production scenarios. therefore, in multiple production scenarios like producing in several production lines with different technologies in a factory, various fitted res...

The use of airplanes for Mars exploration is a new and attractive approach because it provides high resolution power and large spatial coverage. However, it is also a challenging approach in engineering viewpoint. Mars airplanes are required to fly in lower Reynolds number and higher subsonic Mach number conditions due to thinner atmosphere and smaller speed of sound on the Mars, compared to ty...

in a robust parameter design (rpd) problem, the experimenter is interested to determine the values of con-trol factors such that responses will be robust or insensitive to variability of the noise factors. response sur-face methodology (rsm) is one of the effective methods that can be employed for this purpose. since quality of products or processes is usually evaluated through several quality ...

We describe a two-stage robust optimization approach for solving network flow and design problems with uncertain demand. In two-stage network optimization one defers a subset of the flow decisions until after the realization of the uncertain demand. Availability of such a recourse action allows one to come up with less conservative solutions compared to single-stage optimization. However, this ...

We describe a two-stage robust optimization approach for solving network flow and design problems with uncertain demand. In two-stage network optimization, one defers a subset of the flow decisions until after the realization of the uncertain demand. Availability of such a recourse action allows one to come up with less conservative solutions compared to singlestage optimization. However, this ...

This paper presents an innovative optimization approach to solve structural design optimization problems in the automotive industry. The new approach is based on Taguchi’s robust design approach and particle swarm optimization algorithm. The proposed approach is applied to the structural design optimization of a vehicle part to illustrate how the present approach can be applied for solving desi...

The term “robust optimization” is quite popular, and the descriptor “robust” so commonly applied in the water resources literature that its specific meaning, and its implications for model results, have become elusive. We here provide a brief summary of the applications of robust optimization to water resources planning and management problems in the past 15 years. We describe and demonstrate c...