A. Tsoularis

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Abstract: It has been suggested by many supply chain practitioners that in certain cases inventory can have a stimulating effect on the demand. In mathematical terms this amounts to the demand being a function of the inventory level alone. In this work we propose a logistic growth model for the inventory dependent demand rate and solve first the continuous(More)
A variety of growth curves have been developed to model both unpredated, intraspecific population dynamics and more general biological growth. Most predictive models are shown to be based on variations of the classical Verhulst logistic growth equation. We review and compare several such models and analyse properties of interest for these. We also identify(More)
This paper deals with the problem of obstacle avoidance by deviation from the nominal path. Deviation is the only option available to the robot when the acceleration or deceleration plan on the nominal path fails to produce a viable avoidance strategy. The obstacle avoidance on the nominal path was dealt with in our previous development, where the robot’s(More)
In this paper I propose a reinforcement learning model for a predator preying upon two types of prey, the unpalatable (noxious) models, and the palatable mimics. The latter type of prey resembles the models in appearance so as to derive some protection from the predator who must avoid the unpalatable models. Essentially the predator is treated as a learning(More)
In this paper we propose a mathematical learning model for the feeding behaviour of a specialist predator operating in a random environment occupied by two types of prey, palatable mimics and unpalatable models, and a generalist predator with additional alternative prey at its disposal. A well known linear reinforcement learning algorithm and its special(More)
In this paper we propose a mathematical learning model for a stochastic automaton simulating the behaviour of a predator operating in a random environment occupied by two types of prey: palatable mimics and unpalatable models. Specifically, a well known linear reinforcement learning algorithm is used to update the probabilities of the two actions, eat prey(More)
This article considers the deterministic singular optimal control problem of profit maximisation for inventory replenished at a variable rate and depleted by demand which is assumed to vary with price and stock availability. Optimal policies for the product order rate and price are derived using the maximum principle. Several initial inventory regions are(More)
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