inventory model,   backorder   buyer ,   vendor,   lot for lot policy In this paper, an inventory model for two-stage supply chain is investigated. A supply chain with single vendor and single buyer is considered. We assume that shortage as a backorder is allowed for the buyer and the vendor makes the production set up every time the buyer places an order and supplies on a lot for lot basis...

ABSTRACT Surface runoff monitoring is important for the sustainable management of global water resources. Obtaining a practical and inexpensive method collecting data in field can help to better understand surface its effects, necessary watersheds. This study sought elaborate calibration curves ultrasonic sensor due temperature variability, verifying inaccuracy distance between objects sensor, ...

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 ...

This paper presents a method for establishing an optimal network design for the estimation of areal averages of rainfall events. The problem consists of minimising an objective function which includes both the accuracy of the areal mean estimation (as expressed by the kriging variance of estimation) and the economic cost of the data collection. The well known geostatistical variance-reduction m...

Temporal difference learning and Residual Gradient methods are the most widely used temporal difference based learning algorithms; however, it has been shown that none of their objective functions are optimal w.r.t approximating the true value function V . Two novel algorithms are proposed to approximate the true value function V . This paper makes the following contributions: • A batch algorit...

We propose an optimal control approach to tackle large scale unconstrained optimization problems. Our discussion begins with the introduction of a new framework to describe and deene the structure of a general function with a large number of variables. Based on the new concepts, a suucient condition is established so that any large scale unconstrained optimization problem satisfying this suucie...