A SELECTIVE IMPROVEMENT TECHNIQUE FOR FASTENING NEURO-DYNAMIC PROGRAMMING IN WATER RESOURCE NETWORK MANAGEMENT

A Selective Improvement Technique for Fastening Neuro-dynamic Programming in Water Resource Network Management

An approach to the integrated water resources management based on Neuro-Dynamic Programming (NDP) with an improved technique for fastening its Artificial Neural Network (ANN) training phase will be presented. When dealing with networks of water resources, Stochastic Dynamic Programming provides an effective solution methodology but suffers from the so-called “curse of dimensionality”, that rapi...

Neuro-dynamic Programming for the Efficient Integrated Water Resources Management

Design of policies within the integrated water resources management (IWRM) paradigm demands to take into account multiple objectives such as flood protection, water supply for hydropower generation, irrigation and urban use, imposition of minimum environmental flows, etc.. Finding efficient water management policies is a demanding task and Stochastic Dynamic Programming (SDP) can provide an eff...

A Neuro - Dynamic Programming Approach

We formulate the call admission control problem for a single link in an integrated service environment as a Markov Decision Problem. In principle , an optimal admission control policy can be computed using methods of Dynamic Programming. However, as the number of possible states of the underlying Markov Chain grows exponentially in the number of customer classes, Dynamic Programming algorithms ...

A Neuro-Dynamic Programming Approach to Retailer Inventory Management

We present a model of two-echelon retailer inventory systems, and we cast the problem of generating optimal control strategies into the framework of dynamic programming. We formulate two speci c case studies, for which the underlying dynamic programming problems involve thirty-three and forty-six state variables, respectively. Because of the enormity of these state spaces, classical algorithms ...

Neuro-dynamic programming