G. Morganti

A genetic algorithm for the Flexible Job-shop Scheduling Problem

In this paper, we present a genetic algorithm for the Flexible Job-shop Scheduling Problem (FJSP). The algorithm integrates different strategies for generating the initial population, selecting the individuals for reproduction and reproducing new individuals. Computational result shows that the integration of more strategies in a genetic framework leads to better results, with respect to other genetic algorithms. Moreover, results are quite comparable to those obtained by the best-known algorithm, based on tabu search. These two results, together with the flexibility of genetic paradigm, prove that genetic algorithms are effective for solving FJSP.

A simulation environment for the analysis of home automation systems

Using multiple agent system theory, a paradigm for modeling and analyzing home automation systems has been introduced in previous papers. In order to tackle the problem of developing systematic design and validation procedures for control strategies, a rich, versatile simulation/emulation environment is constructed. Global performance indices for the system are introduced and simulation is shown to be an efficient way to estimate them in realistic situations. Relating the indices to suitable control parameters, it is possible to evaluate the efficacy and the efficiency of distributed control strategies and to tune accordingly the control algorithms.

Multi-Agent System Theory for Modelling a Home Automation System

A paradigm for modelling and analysing Home Automation Systems is introduced, based on Multi-Agent System theory. A rich and versatile environment for Home Automation System simulation is constructed for investigating the performances of the system. The exploitation of limited resources (electricity, gas, hot water) depends on behavioural parameters of the individual appliances. In order to deal with the problem of developing systematic design and validation procedures for control strategies, global performance indices for the system are introduced. Different strategies for allocating resources and establishing priorities in their use can therefore be tested and compared.

Optimising Home Automation Systems: A comparative study on Tabu Search and Evolutionary Algorithms

We use the Multi Agent System paradigm to model and analyse Home Automation System performance in exploiting limited resources such as electricity and hot water. In this paper we evaluate several approaches to the optimisation of Home Automation System performance using Tabu Search, and Single and Multi-objective Genetic Algorithms. The results show that the Genetic Algorithms achieve faster convergence than Tabu Search. Multi-objective Genetic Algorithm provides a diverse set of solutions for the decision maker.

Parameter tuning in distributed Home Automation Systems: towards a tabu search approach

This paper deals with the problem of designing an efficient metaheuristics optimization method to tune the parameters of a Home Automation System (HAS). Using a simulation environment, the performances of a home automation system in exploiting limited resources (electricity, gas, hot water) can be described in terms of suitable indices that depend on behavioural parameters of the individual appliances and can be practically evaluated. The choice of the best set of parameters for the model is the common intention of most simulation studies and for this reason in recent years the field of the simulation optimization has received increasing attention. Our method has proven effective in finding good parameter configurations, even starting from very poor initial solutions.

Resource management in home automation systems

This paper deals with the problem of resource management in home automation systems. Since system resources, like electricity and gas, are limited, their concurrent use may cause conflicts that degrade the performances of individual appliances and increase costs or time for accomplishing individual tasks. The general strategy to solve these conflicts consists in determining an order of priority in accessing a given resource when the available amount cannot satisfy the global actual demand. A side effect of this strategy is a loss of efficiency in terms of delays in executing the assigned task, occurring when an appliance must yield and wait until the resource is free. This gives rise to an optimization problem that consists in choosing the best strategy for allocating material resources, respecting constraints and limitations, while minimizing the time required for completing all the tasks in a generic scenario. Either centralized or decentralized control strategies can be employed in this application, using quite different architectures, for managing resources. Here, we propose two control strategies, a centralized one and a decentralized one, which are based, respectively, on game theoretic methods and on off-line optimization by means of genetic algorithms. Performances are compared with respect to generic scenarios and advantages and drawbacks of each one are discussed.

A real-time reliability and durability testing framework

This paper presents a methodological framework for designing testing and measurement systems fully integrated with the enterprise information system. In comparison with the most common solutions for designing embedded testing platforms the proposed framework sets itself at a higher level of abstraction. The proposed framework allows getting different, programmable test benches that can run in parallel, and it does not restrict the choice of hardware, sensors and actuators, as it happens with commercial development systems for the same kind of machines. The framework is conceived to be used on embedded boards equipped with the GNU/Linux operating system and with at least one network interface. By using open data formats, the framework provides an easy way to exchange data with enterprise information systems, thus assuring interoperability with different IT solutions. The paper includes the description of a cooker hood testing system designed and implemented with this framework, and which highlights the advantages of the proposed development method.