Abstract:

The domain of Healthcare is characterized by complexity, dynamics, variety, and fragmentation of distributed medical prevention, diagnosis, treatment, and rehabilitation processes. Healthcare in the 21st century presents enormous challenges (populations are growing and people are living longer) compounding this problem is the widespread lack of skilled caregivers, and the increasing cost of providing. For that, Agent Technology can provide better healthcare than the traditional medical system. In this regard, in this paper we have tried to propose a general architecture that integrates Swarm Intelligence and Multi-Agent System in healthcare in order to make care as efficient as possible.

Abstract:

This paper deals with the real time scheduling techniques for reducing the response time of aperiodic tasks scheduled with real time periodic tasks on uniprocessor systems. Two problems are addressed in this paper: (i) the scheduling of aperiodic tasks when they arrive in order to obtain a feasible system, and (ii) the scheduling of periodic and aperiodic tasks to minimize their response time. In order to improve the responsiveness to both types of problems, efficient approach was proposed based on the Poisson distribution which is a discrete distribution. The Poisson law does not have a fixed number of trials. It uses the fixed interval of time or space in which the number of successes is recorded. The space of feasible deadlines (D-space) is then assumed to be equal to one hour in our proposed approach. The effectiveness and the performance of the designed approach is evaluated through simulation studies.

Abstract:

Starting from a clear proof, which is the relentless increase in demand for travel goods and people need to take better account of modes of transport to this request, the offers of transport systems present in most cases deterministic routes, despite the studies for their modeling, they are often poorly adapted and/or often underutilized The emergence of a new transport demand in areas of low density, transportation of elderly or disabled persons and parcel pick-up and delivery service offered in urban areas has led to the development of another transportation system called dynamic Dial a Ride problem (DRP). The problem is to affect every new passenger request to one of the vehicles and to design a new route and schedule for this vehicle. The dynamic DRP is an NP-hard problem in term of complexity. In addition it is a multi-criteria problem. For these reasons, we propose in this paper a multi agent system as a distributed approach to decompose the problem and to model the heterogeneous vehicle used to solve the problem in concern. Indeed to solve the multi-criteria dynamic DRP, we develop in our multi-agent system a multi-objective simulated annealing algorithm to obtain a Pareto solution for the problem in concern. The process of the proposed approach is shown through an illustrative example.