An optimization approach to wastewater systems planning at regional level

Abstract

A regional wastewater system planning problem consists of finding the minimum-cost configuration for the system needed to drain the wastewater produced at the communities located within a region, while meeting the quality standards defined for the receiving water bodies and complying with all (other) relevant regulatory aspects. There are several possible solutions to this kind of problem. They range from solutions where each community treats its wastewater separately, to solutions where all the wastewater produced in the region is sent to a single treatment plant. It is likely that the most effective solution both in terms of public expenditure, equipment reliability, and environmental impact will be found somewhere between these two extremes. This paper presents an optimization approach to wastewater systems planning at regional level. The approach applies only to sanitary sewer networks. A simulated annealing algorithm is used to solve the optimization model upon which the approach is based. For the application of this approach a user-friendly computing tool was developed. Within this tool, both the acquisition of data and the output of results are made through a flexible GIS interface.

Design of an institutional decision-making process: The case of urban water management

“…The usual optimization software may miss the optimal solution (c.f. Liong and Attiquzzaman, 2004;Sousa et al, 2002;Cisty, 2001;Sherali et al, 2001). -If planners merely report the optimal system as an output of some software, then optimization is like a black box.…”

Siting and sizing the components of a regional wastewater system: a multiobjective approach

“…This was done using three single objective functions: minimize Ci; minimize Ce; maximize DO. The SA algorithm requires the use of accurate parameters, essential for finding good quality solutions (Sousa et al [16]). For the three cases presented, the four SA parameters (α: sets the initial acceptance rate for candidate solutions with value 10% smaller than the value of the incumbent solution, λ: sets the minimum number of candidate solutions that must be evaluated at each temperature, γ: sets the rate at which the temperature decreases, and σ: sets the maximum number of temperature decreases that may occur without an improvement of the best or the average solution value) were calibrated by the authors in previous work (Zeferino et al [22]).…”

“…It describes a multiobjective approach used to solve the siting and the sizing of the different components of a regional wastewater system. The implementation of this approach makes use of the decision-aid model presented in Cunha et al [7].The simulated annealing algorithm (SA) described in Sousa et al [16] improved by a local search algorithm and including the parameters calibrated by Zeferino et al [22] is used.…”

A Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, China

“…Recently, a number of mathematical models related to domestic wastewater management systems have been developed (Butler and Schütze 2005;Chen and Chen 2014;Chen et al 2013;Izquierdo et al 2008;Kang and Lansey 2012;Karuppiah and Grossmann 2006;Park et al 2013;Rojek 2014;Sousa et al 2002). For example, Butler and Schütze (2005) described the development of integrated optimization modelling of the operation and control of urban wastewater management systems, and the results indicated that river quality can be significantly improved by implementing an integrated urban wastewater control strategy.…”