Optimal Control of Industrial Pollution under Stochastic Differential Models

Optimal Control under Stochastic Target Constraints

We study a class of Markovian optimal stochastic control problems in which the controlled process Z is constrained to satisfy an a.s. constraint Z(T ) ∈ G ⊂ R P − a.s. at some final time T > 0. When the set is of the form G := {(x, y) ∈ R × R : g(x, y) ≥ 0}, with g non-decreasing in y, we provide a Hamilton-Jacobi-Bellman characterization of the associated value function. It gives rise to a sta...

Water Pollution Models based on Stochastic Differential Equations

Water pollution has been a crucial problem in many countries and has attracted researcher’s attention from all over the world. In a non-tidal river, from the beginning of material input, mixing and reaction, to the end of material output, the system considered should be dynamic and stochastic. The stochastic differential equation (SDE) is a theory that studies stochastic process. It can describ...

Optimal Control of Upstream Pollution Under Asymmetric Information

This paper derives optimal bribes to reduce upstream transfrontier emissions in the presence of asymmetric information on the polluter’s concern for the environment. In a model in which the starting point for the negotiations on emission reduction is a Cournot-Nash equilibrium, it is shown that transfers from the victim induce the polluting country to exaggerate its concern for the environment....

Pollution Control in Industrial Processes

Modeling and Computation of Transboundary Industrial Pollution with Emission Permits Trading by Stochastic Differential Game

Transboundary industrial pollution requires international actions to control its formation and effects. In this paper, we present a stochastic differential game to model the transboundary industrial pollution problems with emission permits trading. More generally, the process of emission permits price is assumed to be stochastic and to follow a geometric Brownian motion (GBM). We make use of st...