This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP) formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic.
The paper presents a series of experiments in a simulated environment where two autonomous mobile robots gather randomly distributed objects and cluster them into one pile. The coordination of the robots' movements is achieved through stigmergy (an indirect form of communication through the environment). In order to avoid the drawback of the random moves, necessary for stigmergy based foraging behaviour, the perceptive capabilities of the robots are enhanced by detectors for concentration of objects. An artificial immune network carries out the collision free goal following behaviour. Simulations confirm the improved performance of the foraging behaviour under the proposed immune navigation control. Copyright 2005 IFAC
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