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International audience; This study presents a mathematical formulation to optimize contracting capacity strategies of multisources of energy for institutional or industrial consumers considering demand uncertainties. The objective consists of minimizing the total costs composed of the different types of energy contract capacity costs, penalty price, and an ecofriendly factor. The penalty price is charged on the demand of energy exceeding the total contract capacities. The ecofriendly factor encourages the use of renewable energy and reduces the traditional energy used in the optimal mix of energy sources. The proposed model is tested based on demand of energy inspired from real data. These numerical experiments are analyzed to illustrate the impact of encouraging the use of renewable energy sources by introducing the ecofriendly factor and the influence of penalty price and uncertainty in the demand of energy. The results show that in the presence of low penalty price or low uncertainty a large amount of ecofriendly support is needed for using more renewable energy sources in the optimal contract capacity combination.

International audience

International audience; In the field of reliability management, using preventive maintenance is one of the major operations. Optimizing the maintenance policy is required so as to provide a low-cost and efficient function of the system. This paper deals with the problem of maintenance optimization in a multi-states series-parallel system. The objective is to optimize for each system component the maintenance policy minimizing a cost function of the system under the constraint of required availability and for a specified period. Since inspections in the beginning of the life of a component, when the component is very reliable are not efficient, the maintenance policy should identify the dates of first inspection of each system component. We propose using an evolutionary algorithm called fuzzy logic controlled genetic algorithm (FLC-GA) to solve this optimization problem. Two controllers are used to adaptively adjust the crossover and the mutation probabilities based on the fitness function and on the degree of population diversity. Simulation results are presented for the proposed method which is compared to a genetic algorithm with fixed crossover and mutation probabilities. The experimental results show the advantages and the efficiency of FLC-GA.

International audience

International audience

International audience

International audience; The world is getting increasingly complex and we are becoming more and more depending on man-made systems and environments. Failures and lack of function may have increasing consequences to an increasing number of people. In many areas pressure on cost or use of resources is growing. This is a challenge to every organization-how can available resources be used in an effective way. In this situation maintenance optimization is an ever-present issue. In this paper, an optimized maintenance policy for multi state system is presented. Metaheuristics are used as optimisation tools, and the Universal Generating Function and proportional hazard model in system behaviour modelling.

International audience; The world is getting increasingly complex and we are becoming more and more depending on man-made systems and environments. Failures and lack of function may have increasing consequences to an increasing number of people. In many areas pressure on cost or use of resources is growing. This is a challenge to every organization – how can available re-sources be used in an effective way. In this situation maintenance optimization is an ever-present issue. In this paper, an optimized maintenance policy for multi state system is pre-sented. Metaheuristics are used as optimisation tools, and the Universal Generating Function and proportional hazard model in system behaviour modelling.

International audience