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Optimal management of water systems tends to be very complex, especially when water quality aspects are included. This paper addresses the management of multi-quality water networks over a fixed time horizon. The problem is formulated as an optimization program that minimizes cost by determining the optimal flow distribution that satisfies the water quantity and quality requirement in the demand nodes. The resulted model is nonlinear and non-convex due to bilinear terms in the mass balance equations of blending multi-quality flow. This results in several local optima, making the process of solving large-scale problems to global optimality very challenging. One classical approach to deal with this challenge is to use a multi-start procedure in which off-the-shelf local optimization solvers are initialized with several random initial points. Then the final optimal solution is considered as the lowest objective value over the different runs. This will lead to a cumbersome and slow solution process for large-scale problems. In light of the above, this study supports using ultra-fast simple optimization heuristics, which despite their moderate accuracy, can still reach the optimum solution when run many times using a multi-start procedure. As such, the final solution from simple optimization heuristics can compete with off-the-shelf nonlinear solvers in terms of accuracy and efficiency. The paper presents a simple optimization heuristic, which is specially tailored for the problem and compares its performance with a state-of-the-art nonlinear solver on large-scale systems.
Mashor Housh. Optimization of Multi-Quality Water Networks: Can Simple Optimization Heuristics Compete with Nonlinear Solvers? Water 2021, 13, 2209 .
AMA StyleMashor Housh. Optimization of Multi-Quality Water Networks: Can Simple Optimization Heuristics Compete with Nonlinear Solvers? Water. 2021; 13 (16):2209.
Chicago/Turabian StyleMashor Housh. 2021. "Optimization of Multi-Quality Water Networks: Can Simple Optimization Heuristics Compete with Nonlinear Solvers?" Water 13, no. 16: 2209.
Simulation of Water Distribution Networks (WDNs) constitutes a key element for the planning and management of water supply systems. This simulation involves estimating the flows and pressures by solving a linear set of mass conservation equations and a nonlinear set of energy conservation equations. The literature presents different formulations of heads-flows equations to derive the flows and heads in WDN. These formulations differ in terms of dimensionality, computational cost, and solution accuracy. Whereas this problem has been the subject of active research in the past, in the last decades a state of stagnation was reached and no new formulations were introduced. In this study, we propose a novel formulation that utilizes a matrix completion technique to construct a reduced-size nonlinear system of equations that guarantees both mass and energy conservation. Unlike former formulations that rely on the topology of the network, in the proposed method we employ a matrix completion technique in which arbitrary entries are added to the equation system to facilitate its solution. The advantages of the proposed method are demonstrated in simulation and optimization settings. In the former, the method demonstrates improved scalability and accuracy as compared with other widely known formulations. In the latter, the new formulation leads to smaller optimization problems, which are otherwise intractable when the classical formulation is used. Our results reopen an old debate on the best formulation for WDN simulation and optimization tasks and show that the matrix completion technique is a viable solution option for the problem.
Alaa Jamal; Mashor Housh. Utilizing Matrix Completion for Simulation and Optimization of Water Distribution Networks. 2021, 1 .
AMA StyleAlaa Jamal, Mashor Housh. Utilizing Matrix Completion for Simulation and Optimization of Water Distribution Networks. . 2021; ():1.
Chicago/Turabian StyleAlaa Jamal; Mashor Housh. 2021. "Utilizing Matrix Completion for Simulation and Optimization of Water Distribution Networks." , no. : 1.
The common practices for the planning and management of Water Resources Systems (WSSs) have been challenged in the last few decades by global climate change processes, which are observed around the world in increasing frequencies. Climate change is manifested by climate variability, temperature increase, and extreme events such as droughts and floods, which have a decisive effect on natural resource availability and in turn on water quality. Historical records may not be sufficient to reliably account for uncertain future predictions under climate change conditions. While such highly uncertain situations become the “normal” case worldwide, the traditional practices of probabilistic risk measures cannot be used to appropriately quantify the uncertain phenomena under non-stationarity conditions. To better account for uncertain future conditions, the objective of this study is to develop a water management model based on Info-Gap Decision Theory (IGDT) using optimization under deep uncertainty conditions. The Info-Gap theory is a framework that measures the confidence in the operational decisions by quantifying the robustness to uncertainty without accounting for any probabilistic data. To demonstrate the method as a tool to better guide the long-term sustainable operation of the water supply system under uncertain future conditions, we applied the Info-Gap model to the Sea of Galilee (SoG) regional WSS, which is a significant part of the Israeli National Water System (INWS). For Israel, which is, like other Middle East semi-arid regions, prone to dry conditions and limited water availability, there are well-founded concerns that prolonged periods of drought lie ahead, as a consequence of the global climate change processes. This study contributes a management tool for decision making under deep uncertainty to improve the decision-making process and better adapt to unpredictable uncertain future conditions. We demonstrate how the IGDT could be formulated and used to analyze WSSs under different settings and demonstrate how decisions could be derived from the IGDT formulation. We also show a sensitivity analysis for the obtained solutions.
Mashor Housh; Tomer Aharon. Info-Gap Models for Optimal Multi-Year Management of Regional Water Resources Systems under Uncertainty. Sustainability 2021, 13, 3152 .
AMA StyleMashor Housh, Tomer Aharon. Info-Gap Models for Optimal Multi-Year Management of Regional Water Resources Systems under Uncertainty. Sustainability. 2021; 13 (6):3152.
Chicago/Turabian StyleMashor Housh; Tomer Aharon. 2021. "Info-Gap Models for Optimal Multi-Year Management of Regional Water Resources Systems under Uncertainty." Sustainability 13, no. 6: 3152.
Water distribution systems (WDSs) deliver water from sources to consumers. These systems are made of hydraulic elements such as reservoirs, tanks, pipes, valves, and pumps. A pump is characterized by curves which define the relationship of the pump’s head gain and efficiency with its flow. For a new pump, the curves are provided by the manufacturer. However, due to its operating history, the performance of a pump deteriorates, and its curves decline at an estimated rate of about 1% per year. Pump curves are key elements for planning and management of WDSs and for monitoring system efficiency, to determine when a pump should be rehabilitated or replaced. In practice, determining pump curves is done by field tests, which are conducted every few years. This leaves the pump’s performance unmonitored for long time periods. Moreover, these tests often cover only a small range of the curves. This study demonstrates that in the era of IoT and big data, the data collected by Supervisory Control And Data Acquisition (SCADA) systems can be used to continuously monitor pumps’ performance and derive updated pump characteristic curves. We present and demonstrate a practical methodology to estimate fixed and variable speed pump curves in pumping stations. The proposed method can estimate individual pump curves even when the measurements are given only for the pumping station as a whole (i.e., total flow, pumping station head gain). The methodology is demonstrated in a real-world case study of a pumping station in southern Israel.
Elad Salomons; Uri Shamir; Mashor Housh. Optimization Methodology for Estimating Pump Curves Using SCADA Data. Water 2021, 13, 586 .
AMA StyleElad Salomons, Uri Shamir, Mashor Housh. Optimization Methodology for Estimating Pump Curves Using SCADA Data. Water. 2021; 13 (5):586.
Chicago/Turabian StyleElad Salomons; Uri Shamir; Mashor Housh. 2021. "Optimization Methodology for Estimating Pump Curves Using SCADA Data." Water 13, no. 5: 586.
This paper presents a two-stage method for simultaneous least-cost design and operation of looped water distribution systems (WDSs). After partitioning the network into a chord and spanning trees, in the first stage, a reformulated linear programming (LP) method is used to find the least cost design of a WDS for a given set of flow distribution. In the second stage, a non-linear programming (NLP) method is used to find a new flow distribution that reduces the cost of the WDS operation given the WDS design obtained in stage one. The following features of the proposed two-stage method make it more appealing compared to other methods: (1) the reformulated LP stage can consistently reduce the penalty cost when designing a WDS under multiple loading conditions; (2) robustness as the number of loading conditions increases; (3) parameter tuning is not required; (4) the method reduces the computational burden significantly when compared to meta-heuristic methods; and (5) in oppose to an evolutionary “black box” based methodology such as a genetic algorithm, insights through analytical sensitivity analysis, while the algorithm progresses, are handy. The efficacy of the proposed methodology is demonstrated using two WDSs case studies.
Mengning Qiu; Mashor Housh; Avi Ostfeld. A Two-Stage LP-NLP Methodology for the Least-Cost Design and Operation of Water Distribution Systems. Water 2020, 12, 1364 .
AMA StyleMengning Qiu, Mashor Housh, Avi Ostfeld. A Two-Stage LP-NLP Methodology for the Least-Cost Design and Operation of Water Distribution Systems. Water. 2020; 12 (5):1364.
Chicago/Turabian StyleMengning Qiu; Mashor Housh; Avi Ostfeld. 2020. "A Two-Stage LP-NLP Methodology for the Least-Cost Design and Operation of Water Distribution Systems." Water 12, no. 5: 1364.
Flooding of the sewage system is an environmental hazard often caused by illegal connections between drainage and sewage systems. The timely detection of such illicit connections, often done by property owners in an attempt to remove rainwater promptly from their private courtyards, is a complex task due to the high cost of field surveying and limited manpower of environmental law-enforcement authorities. This paper suggests an empirical approach to the identification and characterization of localities with an elevated likelihood of illegal connections between runoff and sewage systems. The proposed approach is implemented in three stages. First, the association between rainfall and the amount of wastewater arriving to sewage treatment facilities from different localities is analyzed. Next, regression residuals are investigated, to identify localities with an especially strong association between the amount of rainfall and sewage surplus. The identified localities are then analyzed, to determine their geographic location, physical and socioeconomic attributes. In the present study, the proposed approach is tested using data for 623 urban and rural localities in Israel. As the study shows, the probability of association between the amount of rainfall and sewage surplus, which we consider as an indicator of pirate connections between drainage and sewage systems, tends to increase as a function of socioeconomic welfare of the local residents, surface slope, and the level of urbanization. The proposed approach can help law-enforcement authorities to focus their efforts on specific locations and to reduce economic and environmental damages associated with illegal connections between drainage and sewage systems.
Rivka Levin; Mashor Housh; Boris A. Portnov. Characterization of Localities with a High Likelihood of Illicit Connections between Runoff and Sewage Systems. Environmental Management 2020, 65, 748 -757.
AMA StyleRivka Levin, Mashor Housh, Boris A. Portnov. Characterization of Localities with a High Likelihood of Illicit Connections between Runoff and Sewage Systems. Environmental Management. 2020; 65 (6):748-757.
Chicago/Turabian StyleRivka Levin; Mashor Housh; Boris A. Portnov. 2020. "Characterization of Localities with a High Likelihood of Illicit Connections between Runoff and Sewage Systems." Environmental Management 65, no. 6: 748-757.
In water distribution systems, pumps are used for supplying water from low points to elevated tanks that supply the network’s demands. The pumps are operated in different ways that could be distinguished by the complexity of the required control system. Such control systems range from pressure and time-based controls, through simple fixed ON-OFF trigger levels (e.g., a bang-bang controller) to complex online pump optimization schemes based on water demand predictions [e.g., the model predictive controller (MPC)]. In this study, we propose an off-line optimization method that utilizes dynamic trigger levels for pump operations. More specifically, these trigger dynamics are optimized according to electricity tariff structure, pump operation conditions, and long demand series in order to allow a more robust operation. We also provide a multiobjective analysis for the optimization problem and analyze the impact of different objectives on the obtained solution. In addition, the methodology is also demonstrated on real-world data.
Mashor Housh; Elad Salomons. Optimal Dynamic Pump Triggers for Cost Saving and Robust Water Distribution System Operations. Journal of Water Resources Planning and Management 2019, 145, 04018095 .
AMA StyleMashor Housh, Elad Salomons. Optimal Dynamic Pump Triggers for Cost Saving and Robust Water Distribution System Operations. Journal of Water Resources Planning and Management. 2019; 145 (2):04018095.
Chicago/Turabian StyleMashor Housh; Elad Salomons. 2019. "Optimal Dynamic Pump Triggers for Cost Saving and Robust Water Distribution System Operations." Journal of Water Resources Planning and Management 145, no. 2: 04018095.
Modern Water Distribution Systems (WDSs) are often controlled by Supervisory Control and Data Acquisition (SCADA) systems and Programmable Logic Controllers (PLCs) which manage their operation and maintain a reliable water supply. As such, and with the cyber layer becoming a central component of WDS operations, these systems are at a greater risk of being subjected to cyberattacks. This paper offers a model-based methodology based on a detailed hydraulic understanding of WDSs combined with an anomaly detection algorithm for the identification of complex cyberattacks that cannot be fully identified by hydraulically based rules alone. The results show that the proposed algorithm is capable of achieving the best-known performance when tested on the data published in the BATtle of the Attack Detection ALgorithms (BATADAL) competition (http://www.batadal.net).
Mashor Housh; Ziv Ohar. Model-based approach for cyber-physical attack detection in water distribution systems. Water Research 2018, 139, 132 -143.
AMA StyleMashor Housh, Ziv Ohar. Model-based approach for cyber-physical attack detection in water distribution systems. Water Research. 2018; 139 ():132-143.
Chicago/Turabian StyleMashor Housh; Ziv Ohar. 2018. "Model-based approach for cyber-physical attack detection in water distribution systems." Water Research 139, no. : 132-143.
Biofuel development to comply with the Renewable Fuel Standard (RFS) would alter conventional crop patterns in agricultural watersheds. As a result, the hydrologic response of the watersheds will exhibit different and often opposing effects on agrohydrological system variables such as riverine nitrate-N load and streamflow. Conventional modeling approaches treat those externalities as regulatory constraints, often fail to consider the hierarchical nature of the decision-making process, and end with unrealistic solutions. This study therefore proposes an alternative decision-modeling framework for biofuel development to optimize a water-quality objective under different levels of streamflow requirement in the watershed. A bilevel programming model is established to mimic the hierarchical decision-making process in environmental regulation. The model is applied to the Sangamon River basin, a typical agricultural watershed in central Illinois, to determine the optimal locations and type of ethanol biorefineries as policy instruments. The results show that the proposed instruments can effectively guide the decisions in biofuel development to meet the environmental objectives in the watershed, although adopting the proposed framework yields a lower profit than the conventional models, which is the price of a more realistic solution to the hierarchical decision problem. The results also highlight the importance of spatial heterogeneity and identifying an appropriate spatial scale to design effective environmental policies in biofuel development.
Majid Shafiee-Jood; Mashor Housh; Ximing Cai. Hierarchical Decision-Modeling Framework to Meet Environmental Objectives in Biofuel Development. Journal of Water Resources Planning and Management 2018, 144, 04018030 .
AMA StyleMajid Shafiee-Jood, Mashor Housh, Ximing Cai. Hierarchical Decision-Modeling Framework to Meet Environmental Objectives in Biofuel Development. Journal of Water Resources Planning and Management. 2018; 144 (7):04018030.
Chicago/Turabian StyleMajid Shafiee-Jood; Mashor Housh; Ximing Cai. 2018. "Hierarchical Decision-Modeling Framework to Meet Environmental Objectives in Biofuel Development." Journal of Water Resources Planning and Management 144, no. 7: 04018030.
This paper presents a modeling framework for real-time decision support for irrigation scheduling using probabilistic seasonal weather forecasts which are incorporated into a simulation-optimization framework. The simulation of the field processes is performed by the Soil Water Atmosphere Plant (SWAP) model, whereas the optimization is performed by three different stochastic programming methods: implicit approach, explicit single-stage approach and explicit two-stage approach. To evaluate the benefit of the probabilistic forecasts, the irrigation schedules from the different stochastic methods are compared with the best benchmark of perfect forecasts as well as with the real field and the Agriculture Extension Service of Israel schedules. The analysis is performed on a real case study of irrigated chickpeas field in Kibbutz Hazorea, Northern Israel. The results show that incorporating stochastic weather forecasts could lead to substantial improvements compared with current irrigation practices.
Alaa Jamal; Raphael Linker; Mashor Housh. Comparison of Various Stochastic Approaches for Irrigation Scheduling Using Seasonal Climate Forecasts. Journal of Water Resources Planning and Management 2018, 144, 04018028 .
AMA StyleAlaa Jamal, Raphael Linker, Mashor Housh. Comparison of Various Stochastic Approaches for Irrigation Scheduling Using Seasonal Climate Forecasts. Journal of Water Resources Planning and Management. 2018; 144 (7):04018028.
Chicago/Turabian StyleAlaa Jamal; Raphael Linker; Mashor Housh. 2018. "Comparison of Various Stochastic Approaches for Irrigation Scheduling Using Seasonal Climate Forecasts." Journal of Water Resources Planning and Management 144, no. 7: 04018028.
CANARY, developed by the U.S. Environmental Protection Agency (USEPA), is a freeware designed for contamination events detection in water distribution systems. CANARY has several imbedded statistical methods for analyzing water quality data to detect contamination events. The imbedded methods require calibration of their parameters to achieve good performance. However, the multiobjective nature of the problem creates a conflict between high sensitivity which results in good detection but with many false alerts, and low sensitivity which results in a small number of false alarms but with poor detection. In this work, a MOGA-CANARY add-in for CANARY autocalibration is introduced. This tool could be used by CANARY users to find the optimal parameter configuration that fits their system. MOGA-CANARY gives the users the whole set of Pareto optimal system configurations based on their defined objectives. The results of MOGA-CANARY are compared with existing manual calibration methods proposed in CANARY documentation.
Mashor Housh; Ziv Ohar. Multiobjective Calibration of Event-Detection Systems. Journal of Water Resources Planning and Management 2017, 143, 06017004 .
AMA StyleMashor Housh, Ziv Ohar. Multiobjective Calibration of Event-Detection Systems. Journal of Water Resources Planning and Management. 2017; 143 (8):06017004.
Chicago/Turabian StyleMashor Housh; Ziv Ohar. 2017. "Multiobjective Calibration of Event-Detection Systems." Journal of Water Resources Planning and Management 143, no. 8: 06017004.
Water distribution systems (WDSs) operation relies on a set of rules and conditions aimed at maintaining a reliable water supply. The WDS operation is often controlled by supervisory control and data acquisition (SCADA) and programmable logic controllers (PLCs). As such, with the SCADA becoming a central component of WDSs these systems can be subjected to cyber-attacks. This paper offer a methodology for identifying cyber-attacks based on logical rules that are based on detailed hydraulic understanding of the WDS combined with a machine learning event detection system for identification of complex cyber-attacks that cannot be fully identified by the hydraulic based rules alone.
Mashor Housh; Ziv Ohar. Model Based Approach for Cyber-Physical Attacks Detection in Water Distribution Systems. World Environmental and Water Resources Congress 2017 2017, 1 .
AMA StyleMashor Housh, Ziv Ohar. Model Based Approach for Cyber-Physical Attacks Detection in Water Distribution Systems. World Environmental and Water Resources Congress 2017. 2017; ():1.
Chicago/Turabian StyleMashor Housh; Ziv Ohar. 2017. "Model Based Approach for Cyber-Physical Attacks Detection in Water Distribution Systems." World Environmental and Water Resources Congress 2017 , no. : 1.
The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time.
Mashor Housh; Ziv Ohar. Integrating physically based simulators with Event Detection Systems: Multi-site detection approach. Water Research 2017, 110, 180 -191.
AMA StyleMashor Housh, Ziv Ohar. Integrating physically based simulators with Event Detection Systems: Multi-site detection approach. Water Research. 2017; 110 ():180-191.
Chicago/Turabian StyleMashor Housh; Ziv Ohar. 2017. "Integrating physically based simulators with Event Detection Systems: Multi-site detection approach." Water Research 110, no. : 180-191.
Least-cost operation of water distribution systems (WDS) is a well-known problem in water distribution systems optimization. The formulation of the problem started with deterministic modeling, and the problem was subsequently handled with more sophisticated stochastic models that incorporate uncertainties related to the problem’s parameters. This work applied a recently developed algorithm entitled limited multistage stochastic programming (LMSP) to deal with the stochastic formulation of the least-cost operation of WDS and serves merely as a proof of concept on an illustrative network. The demand is considered as the uncertain parameter in the problem formulation. This algorithm reduces the complexity of the classical multistage stochastic programming (MSP) by adding constraints which result in a linear growth of the problem, as opposed to an exponential growth in the MSP problem. This is accomplished by clustering decision variables based on a postanalysis of the implicit stochastic program of the problem. The clusters allow reduction of the number of decision variables, thus reducing the complexity of the optimization problem. The LMSP is expected to increase the cost because of the additional constraints imposed on the problem; however, a trade-off exists between the computational complexity and the optimality of the objective value to the number of clusters considered. An illustrative example application is provided for demonstrating the suggested methodology abilities.
Rafael Schwartz; Mashor Housh; Avi Ostfeld. Limited Multistage Stochastic Programming for Water Distribution Systems Optimal Operation. Journal of Water Resources Planning and Management 2016, 142, 06016003 .
AMA StyleRafael Schwartz, Mashor Housh, Avi Ostfeld. Limited Multistage Stochastic Programming for Water Distribution Systems Optimal Operation. Journal of Water Resources Planning and Management. 2016; 142 (10):06016003.
Chicago/Turabian StyleRafael Schwartz; Mashor Housh; Avi Ostfeld. 2016. "Limited Multistage Stochastic Programming for Water Distribution Systems Optimal Operation." Journal of Water Resources Planning and Management 142, no. 10: 06016003.
The three key concepts of interdependency, resiliency and sustainability of a complex system have appeared in a number of studies and in various contexts. Nevertheless, little has been done to define and analyse them, especially the latter two, in a unified quantitative framework for engineering infrastructures. In this paper, we propose overarching mathematical modelling frameworks to quantify these three key concepts in the context of complex infrastructure systems with multiple interdependent subsystems (i.e., the system of systems). We show how interdependencies between subsystems can affect the resiliency and sustainability of the entire system. We provide a case study in the context of biofuel development and use different dynamical models to demonstrate these concepts.
Tri Dung Nguyen; Ximing Cai; Yanfeng Ouyang; Mashor Housh. Modelling infrastructure interdependencies, resiliency and sustainability. International Journal of Critical Infrastructures 2016, 12, 1 .
AMA StyleTri Dung Nguyen, Ximing Cai, Yanfeng Ouyang, Mashor Housh. Modelling infrastructure interdependencies, resiliency and sustainability. International Journal of Critical Infrastructures. 2016; 12 (1/2):1.
Chicago/Turabian StyleTri Dung Nguyen; Ximing Cai; Yanfeng Ouyang; Mashor Housh. 2016. "Modelling infrastructure interdependencies, resiliency and sustainability." International Journal of Critical Infrastructures 12, no. 1/2: 1.
This study addresses the solution of large-scale, non-convex optimization problems with fixed and linear variable costs in the objective function and a set of linear constraints. A successive smoothing algorithm (SSA) is developed to solve a non-convex optimization problem by solving a sequence of approximated convex problems. The performance of the SSA is tested on a series of randomly generated problems. The computation time and the solution quality obtained by the SSA are compared to a mixed integer linear programming (MILP) solver (CPLEX) over a wide variety of randomly generated problems. The results indicate that the SSA performs consistently well and produces high-quality near optimal solutions using substantially shorter time than the MILP solver. The SSA is also applied to solving a real-world problem related to regional biofuel development. The model is developed for a “system of systems” that consists of refineries, transportation, agriculture, water resources and crops and energy market systems, resulting in a large-scale optimization problem. Based on both the hypothetical problems and the real-world application, it is found that the SSA has considerable advantage over the MILP solver in terms of computation time and accuracy, especially when solving large-scale optimization problems.
Mashor Housh; Ximing Cai. Successive smoothing algorithm for solving large-scale optimization models with fixed cost. Annals of Operations Research 2015, 229, 475 -500.
AMA StyleMashor Housh, Ximing Cai. Successive smoothing algorithm for solving large-scale optimization models with fixed cost. Annals of Operations Research. 2015; 229 (1):475-500.
Chicago/Turabian StyleMashor Housh; Ximing Cai. 2015. "Successive smoothing algorithm for solving large-scale optimization models with fixed cost." Annals of Operations Research 229, no. 1: 475-500.
Optimal reservoir operation under uncertainty is a challenging engineering problem. Application of classic stochastic optimization methods to large‐scale problems is limited due to computational difficulty. Moreover, classic stochastic methods assume that the estimated distribution function or the sample inflow data accurately represents the true probability distribution, which may be invalid and the performance of the algorithms may be undermined. In this study, we introduce a Robust Optimization (RO) approach, Iterative Linear Decision Rule (ILDR), so as to provide a tractable approximation for a multi‐period hydropower generation problem. The proposed approach extends the existing LDR method by accommodating nonlinear objective functions. It also provides users with the flexibility of choosing the accuracy of ILDR approximations by assigning a desired number of piecewise linear segments to each uncertainty. The performance of the ILDR is compared with benchmark policies including the Sampling Stochastic Dynamic Programming (SSDP) policy derived from historical data. The ILDR solves both the single and multi‐reservoir systems efficiently. The single reservoir case study results show that the RO method is as good as SSDP when implemented on the original historical inflows and it outperforms SSDP policy when tested on generated inflows with the same mean and covariance matrix as those in history. For the multi‐reservoir case study, which considers water supply in addition to power generation, numerical results show that the proposed approach performs as well as in the single reservoir case study in terms of optimal value and distributional robustness. This article is protected by copyright. All rights reserved.
Limeng Pan; Mashor Housh; Pan Liu; Ximing Cai; Xin Chen. Robust stochastic optimization for reservoir operation. Water Resources Research 2015, 51, 409 -429.
AMA StyleLimeng Pan, Mashor Housh, Pan Liu, Ximing Cai, Xin Chen. Robust stochastic optimization for reservoir operation. Water Resources Research. 2015; 51 (1):409-429.
Chicago/Turabian StyleLimeng Pan; Mashor Housh; Pan Liu; Ximing Cai; Xin Chen. 2015. "Robust stochastic optimization for reservoir operation." Water Resources Research 51, no. 1: 409-429.