Entropy Based Optimization Model of Waste-Load Allocation

2007 ◽  
Author(s):  
Mohammad Karamouz ◽  
Azadeh Ahmadi ◽  
Masoud Taheriyoun
Keyword(s):  
Optimization Model ◽  
Waste Load Allocation ◽  
Waste Load

scholarly journals Fuzzy waste load allocation model: a multiobjective approach

2009 ◽  
Vol 12 (1) ◽  
pp. 83-96 ◽  
Author(s):  
Subimal Ghosh ◽  
P. P. Mujumdar
Keyword(s):  
Water Quality ◽  
Goal Programming ◽  
Optimization Model ◽  
River System ◽  
Base Flow ◽  
Risk Minimization ◽  
Waste Load Allocation ◽  
Allocation Model ◽  
Waste Load ◽  
Input Variables

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, λ, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga–Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Heuristic Algorithms for Waste Load Allocation in a River Basin

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1057-1064 ◽  
Author(s):  
Vijay Joshi ◽  
Prasad Modak
Keyword(s):  
Dynamic Programming ◽  
Heuristic Algorithms ◽  
Water Quality Management ◽  
User Preferences ◽  
Theory And Practice ◽  
Waste Load Allocation ◽  
Practical Applications ◽  
Waste Load ◽  
On Line ◽  
The One

Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.

scholarly journals Fuzzy Optimization Model for Waste Load Allocation in a River with Total Maximum Daily Load (TMDL) Planning

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2618
Author(s):  
Jae Heon Cho ◽  
Jong Ho Lee
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Water Quality Management ◽  
Fuzzy Optimization ◽  
Fuzzy Model ◽  
Low Flow ◽  
Satisfaction Level ◽  
Waste Load Allocation ◽  
Pollutant Load ◽  
Waste Load

In traditional waste load allocation (WLA) decision making, water quality-related constraints must be satisfied. Fuzzy models, however, can be useful for policy makers to make the most reasonable decisions in an ambiguous environment, considering various surrounding environments. We developed a fuzzy WLA model that optimizes the satisfaction level by using fuzzy membership functions and minimizes the water quality management cost for policy decision makers considering given environmental and socioeconomic conditions. The fuzzy optimization problem was formulated using a max–min operator. The fuzzy WLA model was applied to the Yeongsan River basin, which is located in the southwestern part of the Korean Peninsula and Korean TMDLs were applied. The results of the fuzzy model show that the pollutant load reduction should be increased in the Gwangju 1 and Gwangju 2 wastewater treatment plants (WWTPs) and in subcatchments with high pollutant load. In particular, it is necessary to perform advanced wastewater treatment to decrease the load of 932 kg ultimate biochemical oxygen demand (BODu)/day in the large-capacity Gwangju 1 WWTP and reduce the BODu emission concentration from 4.3 to 2.7 mg/L during the low-flow season. The satisfaction level of the fuzzy model is a relatively high at 0.81.

scholarly journals Waste load allocation under uncertainty using game theory approach and simulation-optimization process

2020 ◽  
Vol 22 (4) ◽  
pp. 815-841 ◽  
Author(s):  
Behnam Andik ◽  
Mohammad Hossein Niksokhan
Keyword(s):  
Game Theory ◽  
Sensitivity Analysis ◽  
Simulation Optimization ◽  
Graph Model ◽  
Decision Makers ◽  
Optimization Process ◽  
Theory Approach ◽  
Waste Load Allocation ◽  
Waste Load ◽  
The Status

Abstract This article aims to present a new methodology for waste load allocation (WLA) in a riverine system considering the uncertainty and achieve the lowest amount of inequity index, cost, and fuzzy risk of standard violation. To find a surface of undominated solutions, a new modified PAWN method, initially designed for sensitivity analysis, was developed and coupled with a simulation-optimization process using multi-objective particle swarm optimization (MOPSO) algorithm, to consider the uncertainty of all affecting variables and parameters by using their probability distribution. The proposed methodology applied to Sefidrood River in the northern part of Iran. Graph model for conflict resolution (GMCR) as a subset of game theory was implemented to attain a compromise on WLA among the stakeholders of a river system's quality in Iran: Department of Environment, Municipal Waste Water, and Private Sector. Some undominated solutions were used in GMCR model and modeling the conflict among decision makers reveals that their preferences and the status quo do not lead to a solely stable equilibrium; thus the intervention of a ruler as arbitrator leads them to reach a compromise on a scenario that has a median FRVS and cost. Sensitivity analysis was done using the PAWN method to assess the sensitivity of three intended objectives to all variables and parameters.

Optimizing Multiple-Pollutant Waste Load Allocation in Rivers: An Interval Parameter Game Theoretic Model

2016 ◽  
Vol 30 (12) ◽  
pp. 4201-4220 ◽  
Author(s):  
Mohammad Reza Nikoo ◽  
Pouyan Hatami Bahman Beiglou ◽  
Najmeh Mahjouri
Keyword(s):  
Theoretic Model ◽  
Interval Parameter ◽  
Waste Load Allocation ◽  
Waste Load ◽  
Game Theoretic ◽  
Game Theoretic Model

Optimal water and waste load allocation in reservoir–river systems: a case study

2013 ◽  
Vol 71 (9) ◽  
pp. 4127-4142 ◽  
Author(s):  
Mohammad Reza Nikoo ◽  
Reza Kerachian ◽  
Akbar Karimi ◽  
Ali Asghar Azadnia ◽  
Keighobad Jafarzadegan
Keyword(s):  
Waste Load Allocation ◽  
River Systems ◽  
Waste Load
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