A large number of problems in production planning and scheduling, location, transportation,
finance, and engineering design require that decisions be made in the presence of …

This paper reviews the role of uncertainty in the identification of mathematical models of
water quality and in the application of these models to problems of prediction. More …

The aim of stochastic programming is to find optimal decisions in problems which involve
uncertain data. This field is currently develo** rapidly with contributions from many …

This book is open access under a CC BY-NC 4.0 license. This revised, updated textbook
presents a systems approach to the planning, management, and operation of water …

In science, engineering and economics, decision problems are frequently modelled by
optimizing the value of a (primary) objective function under stated feasibility constraints. In …

Economic growth is frequently considered to be in conflict with sustainable development and
environmental quality. Therefore, a decision maker needs to know how to deal with the …

Several financial planning problems are posed as dynamic generalized network models
with stochastic parameters. Examples include: asset allocation for portfolio selection …

Water resources planners and managers are continually faced with decisions to be made
under uncertainty. In planning problems such as water supply, flood control, and ground …

A stochastic optimization model for containment of a plume of groundwater contamination
through the installation and operation of pum** wells is developed. It considers explicitly …

Recent developments in the area of stochastic programming have resulted in considerable
success in optimal decision making under uncertainty. However, much of the work in this …