Abstract
Consider the problem of deciding whether a set of n sporadic message streams meet deadlines on a Controller Area Network (CAN) bits for a specified priority assignment. It is assumed that message streams have implicit deadlines and no release jitter. An algorithm to solve this problem is well known but unfortunately it time complexity is non-polynomial. We present an algorithm with polynomial time-complexity for computing an tipper bound on the response times. Clearly, if the tipper bound on the response time does not exceed the deadline then all deadlines are met. The pessimism of our approach is proven: if the upper bound of the response time exceeds the deadline then the response time exceeds the deadline as well for a CAN network with half the speed.

Abstract

Abstract
A virtual enterprise (VE) is a temporary organization that pools member enteiprises core competencies and exploits fast changing market opportunities Partner selection can be viewed as a multi-criteria decision making problem that involves, assessing trade-offs between conflicting tangible and intangible criteria, and stating preferences based on incomplete or non-available information. In general, this is a very complex problem due to the large number of alternatives and criteria of different types. In this paper we propose an integrated approach to rank alternative VE configurations using an extension of the TOPSIS method for fuzzy data, improved through the use of a tabu search meta-heuristic. Preliminary computational results clearly demonstrate its potential for practical application.

Abstract
Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable. © World Scientific Publishing Company.

Abstract
Recent advances in neurosciences and psychology have provided evidence that affective phenomena pervade intelligence at many levels, being inseparable from the cognition-action loop. Perception, attention, memory, learning, decisionmaking, adaptation, communication and social interaction are some of the aspects influenced by them. This work draws its inspirations from neurobiology, psychophysics and sociology to approach the problem of building autonomous robots capable of interacting with each other and building strategies based on temperamental decision mechanism. Modelling emotions is a relatively recent focus in artificial intelligence and cognitive modelling. Such models can ideally inform our understanding of human behavior. We may see the development of computational models of emotion as a core research focus that will facilitate advances in the large array of computational systems that model, interpret or influence human behavior. We propose a model based on a scalable, flexible and modular approach to emotion which allows runtime evaluation between emotional quality and performance. The results achieved showed that the strategies based on temperamental decision mechanism strongly influence the system performance and there are evident dependency between emotional state of the agents and their temperamental type, as well as the dependency between the team performance and the temperamental configuration of the team members, and this enable us to conclude that the modular approach to emotional programming based on temperamental theory is the good choice to develop computational mind models for emotional behavioral Multi-Agent systems.

Abstract
In the previous paper of this series [Vasili et al., 2006. Comparison of different dwell point policies for SP-AS/RS. Int J of Eng and Tech, 3(1):91-106], two reliable travel time models for SP-AS/RS under return to middle and return to start, dwell point policies were developed and presented based on the continuous rack approximation approach. In this paper, the authors present an alternative configuration for the input/output (I/O) station in SPAS/ RS, in order to reduce average handling time of this system. A travel time model is developed for this new configuration and the accuracy of the model is validated by Monte Carlo simulation. The results of new model and previous models are compared and the best policy is introduced. The results show that in a range of shapes (when shape factor is less than or equal to 2), new configuration of SP-AS/RS is more preferable.