Multiprocessor implementation of Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution System - a new water quality model approach

The Critical Infrastructure Systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classified as large scale complex systems of network structure, influenced by strong interactions form the surrounding environment, internal and external interconnections. The later is a result of inter-CIS dependencies. The control, monitoring and control of these system is crucial to guaranty safe access to the resources distributed by the means of CIS. Among those systems the Drinking Water Distribution System (DWDS) may be found – a nonlinear dynamic carrier-load networked system. To handle these systems in a proper (robustly feasible) manner one needs to consider a nontrivial control task complimented by a set of input and state constraints. This surely points to model predictive optimal control schemes. To carry on the control a set of actuators – disinfectant booster stations – needs to be allocated within the DWDS to enable the control system to be robustly feasible. The task of optimised allocation has been addressed within this paper based on old (linear) and new (nonlinear) quality models in order to determine the impact of model structure and thus precision on the allocation results. The allocation task is formulated as a multiobjective, nonlinear/linear mixed-integer optimisation problem to be solved by a genetic algorithm (implementation of NSGA-II) due to nature of the problem. The newly obtained numerical examples are to illustrate the results. For this purpose a Chojnice (city in northern Poland) DWDS case study plant was utilised.