Generalized Network Algorithm for Water-Supply-System Optimization

Abstract

In recent years, considerable progress has been made in the development of fast network flow algorithms aiming at solving linear programming problems with network substructures. Recognizing the fact that the basic structure of a water-supply system is a network, network algorithms have been used for system operation and management. However, to date, most algorithms are designed to solve transshipment problems in a pure network setting with total demand being equal to total supply. The non–network-type constraints and variables are precluded from the network models. Consequently, network models are used to perform optimization only for the network portion of the water-supply system under certain overall operational guidelines. In this study, an algorithm, EMNET, is introduced for solving the regional-water-supply-system optimization that corresponds to a generalized network problem with additional non–network-type constraints and non–network-type variables. The multiperiod, multiobjective optimization model for the regional water-supply system of the Metropolitan Water District of Southern California is used for case study. The results show that, depending on the network substructure in the model, EMNET is 11–117 times faster than standard linear programming codes, such as MINOS.