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Showing 3 results for Multi-Objective Optimization

K. Behzadian, M. Alimohammadnejad, A. Ardeshir, H. Vasheghani, F. Jalilsani,
Volume 10, Issue 1 (3-2012)
Abstract

Compared to conventional chlorination methods which apply chlorine at water treatment plant, booster chlorination has almost

solved the problems of high dosages of chlorine residuals near water sources and lack of chlorine residuals in the remote points

of a water distribution system (WDS). However, control of trihalomethane (THM) formation as a potentially carcinogenic

disinfection by-product (DBP) within a WDS has still remained as a water quality problem. This paper presents a two-phase

approach of multi-objective booster disinfection in which both chlorine residuals and THM formation are concurrently optimized

in a WDS. In the first phase, a booster disinfection system is formulated as a multi-objective optimization problem in which the

location of booster stations is determined. The objectives are defined as to maximize the volumetric discharge with appropriate

levels of disinfectant residuals throughout all demand nodes and to minimize the total mass of disinfectant applied with a specified

number of booster stations. The most frequently selected locations for installing booster disinfection stations are selected for the

second phase, in which another two-objective optimization problem is defined. The objectives in the second problem are to

minimize the volumetric discharge avoiding THM maximum levels and to maximize the volumetric discharge with standard levels

of disinfectant residuals. For each point on the resulted trade-off curve between the water quality objectives optimal scheduling of

chlorination injected at each booster station is obtained. Both optimization problems used NSGA-II algorithm as a multi-objective

genetic algorithm, coupled with EPANET as a hydraulic simulation model. The optimization problems are tested for different

numbers of booster chlorination stations in a real case WDS. As a result, this type of multi-objective optimization model can

explicitly give the decision makers the optimal location and scheduling of booster disinfection systems with respect to the tradeoff

between maximum safe drinking water with allowable chlorine residual levels and minimum adverse DBP levels.


M. Abbasi, A. H. Davaei Markazi,
Volume 12, Issue 1 (3-2014)
Abstract

An important factor in the design and implementation of structural control strategies is the number and placement of actuators. By employing optimally-located actuators, the effectiveness of control system increases, while with an optimal number of actuators, an acceptable level of performance can be achieved with fewer actuators. The method proposed in this paper, simultaneously determines the number and location of actuators, installed in a building, in an optimal sense. In particular, a genetic algorithm which minimizes a suitably defined structural damage index is introduced and applied to a well-known nonlinear model of a 20-story benchmark building. It is shown in the paper that an equal damage protection, compared to the work of other researchers, can be achieved with fewer numbers of optimally placed actuators. This result can be important from economic point of view. However, the attempt to minimize one performance index has negative effect on the others. To cope with this problem to some extent, the proposed genetic methodology has been modified to be applied in a multi-objective optimization problem.
Laemthong Laokhongthavorn, Chalida U-Tapao,
Volume 15, Issue 2 (3-2017)
Abstract

This paper has applied operation research to solid waste disposal by which two objective functions are optimized to minimize the expected operational costs (maximize revenues) and the expected net carbon dioxide equivalent (CDE) emissions. Types and uncertain amounts of solid wastes as well as costs of electricity were factored into the selection decision of solid waste disposal, i.e. landfill, incineration, composting and recycling. An optimization model was applied to the solid waste disposal of Bangkok, Thailand. In addition, a multi-objective optimization technique was proposed for a tradeoff decision-making between minimum operational costs and CDE emissions. Composting and landfill are effective alternatives for Bangkok’s solid waste disposal system. The operational costs and net CDE emissions are highly correlated with the quantity of solid waste. Policy-makers and plant operators could adopt the proposed optimization model under uncertainty in the selection of an optimal solid waste disposal.



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