In this letter we consider a distributed stochastic optimization framework in which agents network aim to cooperatively learn an optimal network-wide policy. The goal is compute local functions minimize the expected value of given cost, subject individual constraints and average coupling constraints. order handle challenges context, resort Lagrangian duality approach that allows us derive assoc...

In the present economic context, the operating theater is considered as a critical activity in health care management. This paper describes a model for operating room (OR) planning under constraint of a unique equipment. At first level we schedule elective surgeries under the uncertainty of using a unique equipment. At the second level we consider emergency surgeries, and at the third le...

This study proposes a new multi-item inventory model with hybrid cost parameters under a fuzzy-stochastic constraint and permissible delay in payment. The price and marketing expenditure dependent stochastic demand and the demand dependent the unit production cost are considered. Shortages are allowed and partially backordered. The main objective of this paper is to determine selling price, mar...

Many artificial intelligence tasks (e.g., planning, situation assessment, scheduling) require reasoning about events in time. Temporal constraint networks offer an elegant and often computationally efficient framework for formulation and solution of such temporal reasoning tasks. Temporal data and knowledge available in some domains is necessarily imprecise e.g., as a result of measurement erro...

In this work we introduce a novel approach, based on sampling, for finding policies that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems. Our approach reduces the size of the original problem being analysed and it guarantees that, with a given confidence probability, the policies produced by solving this reduced problem satisfy the ...

Automatic structural test data generation is a real challenge of Software Testing. Statistical structural testing has been proposed to address this problem. This testing method aims at building an input probability distribution to maximize the coverage of some structural criteria. Under the all paths testing objective, statistical structural testing aims at selecting each feasible path of the p...