scholarly journals Multi-objective optimization for sustainable groundwater management by developing of coupled quantity-quality simulation-optimization model

2017 ◽  
Vol 19 (6) ◽  
pp. 973-992 ◽  
Author(s):  
Asghar Kamali ◽  
Mohammad Hossein Niksokhan
Keyword(s):  
Water Quality ◽  
Optimization Model ◽  
Simulation Optimization ◽  
Simulation Models ◽  
Multi Objective Optimization ◽  
Management Scenarios ◽  
Sustainability Index ◽  
Multi Objective ◽  
Previous Operation ◽  
The Stability

Abstract This study addresses the issue of optimal management of aquifers using a mathematical simulation- optimization model which relies on the stability of water quality and quantity, considering salinity. In this research first we developed a hydrological model (SWAT) to estimate recharge rates and its spatiotemporal distribution. Then, groundwater simulation of the basin was simulated and calibrated using MODFLOW 2000 and water quality was simulated and calibrated using MT3DMS. Afterwards, a multi-objective optimization model (MOPSO) and embed simulation models as tools to assess the objective function was carried out in order to produce a simulation-optimization model. Finally, a sustainability index to assess Pareto front's answers and three management scenarios (continuing previous operation, 30% increasing and reduction in previous operation) was developed. The results show that the majority of Pareto optimal answers have more sustainability index than a 30% reduction of operation with the best answer of 0.059. Relatively, the sustainability index of 30% reduction of operation is 0.05.

scholarly journals A multi-objective optimization model for operation of intermittent water distribution networks

2020 ◽  
Vol 20 (7) ◽  
pp. 2630-2647
Author(s):  
Mohammad Solgi ◽  
Omid Bozorg-Haddad ◽  
Hugo A. Loáiciga
Keyword(s):  
Water Quality ◽  
Water Supply ◽  
Optimization Model ◽  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Intermittent Operation ◽  
Supply Interruption

Abstract Intermittent operation of water distribution networks (WDNs) is an undesirable yet inevitable strategy under some circumstances such as droughts, development, electricity blackouts, and water pollution, mostly in developing countries. Intermittent utilization of WDNs poses several disadvantages encompassing water quality degradation, deterioration of the water-distribution system, and extra operational and maintenance costs due to frequently interrupted supply, unfair water distribution among consumers, and reduction of system serviceability. This paper proposes a multi-objective optimization model to address the negative consequences of intermittent water shortages. The model is intended to maximize the quantitative and qualitative reliability and the fairness in water supply, and to minimize the frequency of supply interruption. The developed model also considers pragmatic limitations, water quality, water pressure, and supply reservoir's constraints to plan the operation of intermittent water distribution systems under water shortage. The model's efficiency is tested with a WDN in Iran and compared with a standard operation policy (SOP) for water distribution. According to the evaluated efficiency criteria concerning reliability, resiliency, and vulnerability of water quality and quantity of water supply, the developed model is superior to the SOP rule and improves the performance of the network under intermittent operation. In addition, the results demonstrate there is a tradeoff between the uniformity of water distribution and the frequency of supply interruption that shows operators’ and customers’ conflicting priorities.

Adaptive multi-objective simulation–optimization framework for dynamic flood control operation in a river–reservoir system

2015 ◽  
Vol 46 (6) ◽  
pp. 893-911 ◽  
Author(s):  
Om Prakash ◽  
K. Srinivasan ◽  
K. P. Sudheer
Keyword(s):  
Optimization Model ◽  
Flood Control ◽  
Simulation Optimization ◽  
Control Point ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Control Operation ◽  
Multi Objective ◽  
River Reservoir ◽  
Flood Control Operation

An adaptive simulation–optimization (S–O) framework enables dynamic reservoir operational decision-making process during the different phases (time stages) of flood control operation during the passage of a flood event in a river–reservoir system is proposed. This is achieved by incorporating the changing priorities of the reservoir operator/manager at each phase of the flood mitigation operation into the S–O framework by evoking the appropriate set of objective functions and dynamically reconstructing the multi-objective optimization model. Five different objective functions are formulated within the S–O framework, out of which two are concerned with the mitigation at the reservoir; two more deal with the mitigation at the control point; and one ensures sufficient water is stored for meeting future demands. The non-dominated sorting genetic algorithm-II (NSGA-II) is employed to obtain the trade-off solutions from the multi-objective optimization model at each time stage. The results from the study show that the dynamic flood operation model yields a significant level of improvement in flood peak mitigation over the static model both at the reservoir as well as at the control point. The proposed S–O framework can be used in developing either deterministic or probabilistic optimal reservoir release policies for flood control operation, especially where damage functions and penalty functions are not developed.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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