Active Robust Optimization: Enhancing Robustness to Uncertain Environments
نویسندگان
چکیده
منابع مشابه
On Robustness Criteria and Robust Topology Optimization with Uncertain Loads
We propose a new algorithm for the solution of the robust multiple-load topology optimization problem. The algorithm can be applied to any type of problem, e.g., truss topology, variable thickness sheet or free material optimization. We assume that the given loads are uncertain and can be subject to small random perturbations. Furthermore, we define a rigorous measure of robustness of the given...
متن کاملOptimization in Uncertain and Complex Dynamic Environments with Evolutionary Methods
In the real world, many of the optimization issues are dynamic, uncertain, and complex in which the objective function or constraints can be changed over time. Consequently, the optimum of these issues is changed nonlinearly. Therefore, the optimization algorithms not only should search the global optimum value in the space but also should follow the path of optimal change in dynamic environmen...
متن کاملRobust Planning in Uncertain Environments
This paper describes a novel approach to planning which takes advantage of decision theory to greatly improve robustness in an uncertain environment. We present an algorithm which computes conditional plans of maximum expected utility. This algorithm relies on a representation of the search space as an AND/OR tree and employs a depth-limit to control computation costs. A numeric robustness fact...
متن کاملEnsuring Robust Agent Control in Uncertain Environments
Agent control involves reasoning about local problem solving ac tivities interacting with other agents planning for a course of action and contingencies in the event of failure of the action and nally carry ing out the actions with limited resources and uncertainty about agent outcomes and the actions of other agents The growing complexity and dynamics of agents and the environments in which th...
متن کاملEnhancing Evolutionary Optimization in Uncertain Environments by Allocating Evaluations via Multi-armed Bandit Algorithms
Optimization problems with uncertain fitness functions are common in the real world, and present unique challenges for evolutionary optimization approaches. Existing issues include excessively expensive evaluation, lack of solution reliability, and incapability in maintaining high overall fitness during optimization. Using conversion rate optimization as an example, this paper proposes a series...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Cybernetics
سال: 2014
ISSN: 2168-2267,2168-2275
DOI: 10.1109/tcyb.2014.2304475