A general approach to online network optimization problems
نویسندگان
چکیده
منابع مشابه
A General Evolutionary/Neural Hybrid Approach to Learning Optimization Problems
A method combining the parallel search capabilities of Evolutionary Computation (EC) with the generalization of Neural Networks (NN) for solving learning optimization problems is presented. Assuming a fitness function for potential solutions can be found, EC can be used to explore the solution space, and the survivors of the evolution can be used as a training set for the NN which then generali...
متن کاملStatistical Cooling: a General Approach to Combinatorial Optimization Problems
Statistical cooling is a new combinatorial optimization technique based on Monte-Carlo iterative improvement. The method originates from the analogy between the annealing of a solid as described by the theory of statistical physics and the optimization of a system with many degrees of freedom. In the present paper we present a general theoretical framework for the description of the statistical...
متن کاملA Chance Constraint Approach to Multi Response Optimization Based on a Network Data Envelopment Analysis
In this paper, a novel approach for multi response optimization is presented. In the proposed approach, response variables in treatments combination occur with a certain probability. Moreover, we assume that each treatment has a network style. Because of the probabilistic nature of treatment combination, the proposed approach can compute the efficiency of each treatment under the desirable reli...
متن کاملA General Iterative Approach to Variational Inequality Problems and Optimization Problems
We introduce a new general iterative scheme for finding a common element of the set of solutions of variational inequality problem for an inverse-strongly monotone mapping and the set of fixed points of a nonexpansive mapping in a Hilbert space and then establish strong convergence of the sequence generated by the proposed iterative scheme to a common element of the above two sets under suitabl...
متن کاملA continuous-time approach to online optimization
We consider a family of learning strategies for online optimization problems that evolve in continuous time and we show that they lead to no regret. From a more traditional, discrete-time viewpoint, this continuous-time approach allows us to derive the no-regret properties of a large class of discretetime algorithms including as special cases the exponential weight algorithm, online mirror desc...
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: ACM Transactions on Algorithms
سال: 2006
ISSN: 1549-6325,1549-6333
DOI: 10.1145/1198513.1198522