In this paper, a solution procedure has been given for the Chance Constrained Programming Models For Multi-Objective Interval Solid Transportation Problem under stochastic environment (MOISTP) where the cost coefficients of the objective functions, the source availability, destination demand and conveyance capacities have been taken as stochastic intervals by the decision makers. The problem ha...

If there are grey variables in the constraint conditions in uncertain programming, the programming is called grey chance constrained programming. In this paper we provide the concept of grey chance constrained programming. When the whitenization weight functions of grey variables are known and the distribution functions are constructed, we studied the certainty equivalence solution of grey chan...

one of the most important measures needed to be done in times of crisis is to optimize the allocation and distribution of resources among individuals. time is a critical factor effective to increase the number of people rescued by the relief activities.in this paper, we present a relief vehicle routing model in the affected area which uses covering tour approach to reduce total response time. a...

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 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...

It is challenging to generate optimal trajectories for nonlinear dynamic systems under external disturbances. In this brief, we present a novel approach planning safe of the chance-constrained trajectory optimization problems with nonconvex constraints. First, chance constraints are handled by deterministic ones which show its availability. We derive an iterative convex method solve control pro...

Multi-objective programming with uncertain information has been widely applied in modeling of industrial produce and logistic distribution problems. Usually the expectation value model and chance-constrained model as solution models are used to deal with such uncertain programming. In this paper, we consider the uncertain programming problem which contains random information and rough informati...