Summarization: The optimal size of k is specified for two-state k-out-of-n systems that may be functioning or fail in either state. It is assumed that the steady-state, success and failure probabilities are not known exactly. The problem is reduced to finding the saddle-point solution to a minimax optimization problem. An example shows that the minimax design is robust with regard to uncertainty.Presented on: Applied Stochastic Models and Data Analysi
Some new properties and computational tools for finding KL-optimum designs are provided in this pape...
In a multi-state consecutive-k-out-of-n:F system, both the components and the system are allowed to ...
A control problem with a system modeled as a nondeterministic finite state machine is considered. Se...
[[abstract]]In this thesis, we are interested in finding optimal minimax designs for heteroscedastic...
The present paper is aimed at finding the best compromise to design a system k-out-of-n reliability ...
Design of complex physical systems most often relies on numerical simulations that may be extremely ...
This Thesis is a fundamental investigation of minimax approaches to robust control. The minimax game...
Abstract In this paper, we consider the decision problem that an automated control system faces when...
We consider an optimization problem in which some uncertain parmeters are replaced by random variabl...
Controlling a system with control and state constraints is one of the most important problems in con...
Maximum variance (MV) and Standarized maximum variance (SMV) optimum designs for binary response mod...
This thesis develops and utilizes the cost-to-come methodology for the construction of minimax contr...
This thesis addresses the problem of worst-case steady-state design of process systems under uncerta...
International audienceWorst-case design is important whenever robustness to adverse environmental co...
Decision makers must often base their decisions on incomplete (coarse) data. Recent research has sho...
Some new properties and computational tools for finding KL-optimum designs are provided in this pape...
In a multi-state consecutive-k-out-of-n:F system, both the components and the system are allowed to ...
A control problem with a system modeled as a nondeterministic finite state machine is considered. Se...
[[abstract]]In this thesis, we are interested in finding optimal minimax designs for heteroscedastic...
The present paper is aimed at finding the best compromise to design a system k-out-of-n reliability ...
Design of complex physical systems most often relies on numerical simulations that may be extremely ...
This Thesis is a fundamental investigation of minimax approaches to robust control. The minimax game...
Abstract In this paper, we consider the decision problem that an automated control system faces when...
We consider an optimization problem in which some uncertain parmeters are replaced by random variabl...
Controlling a system with control and state constraints is one of the most important problems in con...
Maximum variance (MV) and Standarized maximum variance (SMV) optimum designs for binary response mod...
This thesis develops and utilizes the cost-to-come methodology for the construction of minimax contr...
This thesis addresses the problem of worst-case steady-state design of process systems under uncerta...
International audienceWorst-case design is important whenever robustness to adverse environmental co...
Decision makers must often base their decisions on incomplete (coarse) data. Recent research has sho...
Some new properties and computational tools for finding KL-optimum designs are provided in this pape...
In a multi-state consecutive-k-out-of-n:F system, both the components and the system are allowed to ...
A control problem with a system modeled as a nondeterministic finite state machine is considered. Se...