In this paper, a model of an optimal control problem with chance constraints is introduced. The parametersof the constraints are fuzzy, random or fuzzy random variables. Todefuzzify the constraints, we consider possibility levels.  Bychance-constrained programming the chance constraints are converted to crisp constraints which are neither fuzzy nor stochastic and then the resulting classical op...

The Chance-Constrained Stochastic Programming (CCSP) is one of the models for decision making under uncertainty. In this paper, we consider the special case of the CCSP in which only the righthand side vector is random with a discrete distribution having a finite support. The unit commitment problem is one of the applications of the special case of the CCSP. Existing methods for exactly solving...

This thesis presents an algorithm that eliminates square root and division op-erations in some straight-line programs used in embedded systems while pre-serving the semantics. Eliminating these two operations allows to avoid errorsat runtime due to rounding. These errors can lead to a completely unexpectedbehavior from the program. This transformation respects the constraint...

Geometric programming is efficient tool for solving a variety of nonlinear optimizationproblems. Geometric programming is generalized for solving engineering design. However,Now Geometric programming is powerful tool for optimization problems where decisionvariables have exponential form.The geometric programming method has been applied with known parameters. However,the observed values of the ...

In chance-constrained optimization problems, a solution is assumed to be feasible only with certain, sufficiently high probability. For computational and theoretical purposes, the convexity property of the resulting constraint set is treated. It is known, for example, that a suitable combination of a concavity property of the probability distribution and concavity of constraint mappings are suf...

There are many cases that a nonlinear fractional programming, generated as a result of studying fractional stochastic programming, must be solved. Sometimes an approximate solution may be sufficient enough to start a new process of calculations. To this end, this author introduces a new linear approximation technique for solving a fractional chance constrained programming (CCP) problem. After i...

Stochastic Approach to Vehicle Routing Problem: Development and Theories Abstract In this article, a chance constrained (CCP) formulation of the Vehicle Routing Problem (VRP) is proposed. The reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. Knowing that reliable computer software...

Aspect-Oriented Programming (AOP) promises separation of concerns at the implementation level. However, aspects are not always orthogonal and aspect interaction is an important problem. Currently there is almost no support for the detection and resolution of such interactions. The programmer is responsible for identifying interactions between con icting aspects and implementing con ict resoluti...

In this article, we present a framework for planning an activity to be executed with the support of robotic navigation assistant. The two main components are and motion planner. planner composes sequence abstract activities, chosen from given set, synthesize plan. Each is associated point interest in environment probabilistic parameters that depend on plan, which characterized by simulations re...