This paper presents a sequential semidefinite programming (SDP) approach to maximize the minimal eigenvalue of the generalized eigenvalue problem, in which the two symmetric matrices defining the eigenvalue problem are supposed to be the polynomials in terms of the variables. An important application of this problem is found in the structural optimization which attempts to maximize the minimal ...

artificial neural networks are used in many smart apparatus and different fields such as signal processing pattern diagnoses, military systems, medicine, financial systems, and artificial intelligence. in this article using quality of neural networks in optimizing energy cost in moving limb and its effectiveness in organization a cognitive function founded by presenting an algorithm for use in ...

In this classic book Richard Bellman introduces the reader to the mathe­ matical theory of his subject, dynamic programming. His goal is to show how multistage decision processes, occurring in various kinds of situations of concern to military, business, and industrial planners and to economists, are amenable to mathematical analysis. Written during the infancy of high­ speed, large­capacity di...

Designing effective aviation security systems has become a problem of national concern. Passenger screening is an important component of aviation security. Developing real-time passenger screening strategies can be quite challenging. This paper identifies a methodology that can be used in real-time to optimally assign passengers to aviation security resources for the Sequential Stochastic Multi...

Sequential Decision Making (SDM) problems optimize over the sequence of actions (or, decisions) taken to minimize underlying cumulative cost. These are referred as policy SDM. Often these comprise additional (fixed and manipulable) parameters; objective is determine optimal well manipulable parameters that minimizes SDM In this paper we address class characterized by dynamic where dynamics pre-...

A symbolic dynamic programming approach for modelling first-order Markov decision processes within the fluent calculus is given. Based on an idea initially presented in [3], the major components of Markov decision processes such as the optimal value function and a policy are logically represented. The technique produces a set of first-order formulae with equality that minimally partitions the s...

We consider an inventory model for spare parts with two stockpoints, providing repairable parts for a critical component of advanced technical systems. As downtime costs for these systems are huge, ready-for-use spare parts are kept on stock, to be able to quickly respond to a breakdown of a system. We allow for lateral transshipments of parts between the stockpoints upon a demand arrival for a...

The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficu...

Abstract Selective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there situations the system needs small intervals or break for actions, during expert carried out actions to replace repair deteriorated components systems. Because uncertainty associated with component’s operational time, fa...