Project scheduling problem is mainly to determine the schedule of allocating resources in order to balance the total cost and the completion time. This paper chiefly uses chance theory to introduce project scheduling problem with uncertain variables. First, two types of single-objective programming models with uncertain variables as uncertain chance-constrained model and uncertain maximization ...

This paper analyses the requirements of a toolset intended for integrated parallel system design Real time data dominated systems are targeted particularly those in vision and image processing A con strained abstract model is represented based around software pipelines each stage of which can contain a parallel component The toolset is novel in seeking to enable generalized parallelism in which...

background: aflatoxin m1 (afm1) is a toxic compound that could be found in milk and dairy products. afm1 is the principle hydroxylated derivative of aflatoxin b1 (afb1), formed in liver and excreted into the milk in the mammary glands of both human and lactating animals that have been fed with afb1 contaminated diet. to the best of our knowledge, there is no report on stability of afm1 during p...

This paper is concerned with chance constrained programming to deal with nonlinear optimization problems with random parameters. Specific Monte Carlo methods to evaluate the gradient and Hessian of probabilistic constraints are proposed and discussed. These methods are implemented in penalization optimization routines adapted to stochastic optimization. They are shown to reduce the computationa...

This paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. Since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzz...

in this paper, we deal with fuzzy random variables for inputs andoutputs in data envelopment analysis (dea). these variables are considered as fuzzyrandom flat lr numbers with known distribution. the problem is to find a method forconverting the imprecise chance-constrained dea model into a crisp one. this can bedone by first, defuzzification of imprecise probability by constructing a suitablem...