M. Ehsan Shafiee

An evolutionary algorithm approach to generate distinct sets of non-dominated solutions for wicked problems

Many engineering design problems must optimize multiple objectives. While many objectives are explicit and can be mathematically modeled, some goals are subjective and cannot be included in a mathematical model of the optimization problem. A set of alternative non-dominated fronts that represent multiple optima for problem solution can be identified to provide insight about the decision space and to provide options and alternatives for decision-making. This paper presents a new algorithm, the Multi-objective Niching Co-evolutionary Algorithm (MNCA) that identifies distinct sets of non-dominated solutions which are maximally different in their decision vectors and are located in the same non-inferior regions of a Pareto front. MNCA is demonstrated to identify a set of non-dominated fronts with maximum difference in decision vectors for a set of real-valued problems.

Integrating evolutionary computation and sociotechnical simulation for flushing contaminated water distribution systems

A water distribution contamination event occurs when a chemical or pathogen is introduced to a pipe network dedicated to the delivery of potable water. During an event, complex interactions among consumers, utility operators, decision makers, and the pipe network can influence the number of exposed consumers, as human actors adapt their water use activities in response to warnings or exposure. An agent-based model is developed to model the water contamination event and provides insight and understanding about the effect of interactions on public health, such as the number of exposed consumers. Utility operators can protect consumers using a wide range of mitigation responses, and opening a set of hydrants is typically an effective strategy for flushing contaminated water before it reaches consumers. The ABM framework is coupled with an Evolutionary Strategy (ES)-based search to identify an optimal strategy for manipulating hydrants to minimize the number of exposed consumers. The application of the simulation-optimization framework is demonstrated for a virtual mid-sized municipality, Mesopolis.

Parallel Evolutionary Algorithm for Designing Water Distribution Networks to Minimize Background Leakage

AbstractLeaks in water distribution systems waste energy and water resources, increase damage to infrastructure, and may allow contamination of potable water. This research develops an evolutionary algorithm-based approach to minimize the cost of water loss, new infrastructure, and operations that reduce background leakage. A new design approach is introduced that minimizes capital and operational costs, including energy and water loss costs. Design decisions identify a combination of infrastructure improvements, including pipe replacement and valve installment, and operation rules for tanks and pumps. Solution approaches are developed to solve both a single-objective and multiobjective problem formulation. A genetic algorithm and a nondominated sorting genetic algorithm are implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure-reducing valves, and pipe diameters for replacing pipes. The evolutionary algorithm approaches identif...

Real-Time Guidance for Hydrant Flushing Using Sensor-Hydrant Decision Trees

AbstractA utility may detect contaminant in a water distribution network through water quality sensor information, which indicates that a biological pathogen or chemical contaminant is present in the network. A utility manager should identify actions that can be taken to protect public health, and flushing a contaminant by opening a set of hydrants can be an effective response action. Hydrants should be selected and timed to flush the contaminant; however, accurately ascertaining the characteristics of the contaminant source may be impossible, which creates difficulties in developing a hydrant flushing strategy. This research develops a decision-making approach that is designed to select hydrant flushing strategies in response to sensor activations and does not require information about the characteristics of the contaminant source. A sensor-hydrant decision tree is introduced to provide a library of rules for opening and closing hydrants based on the order of activated sensors. Sensor-hydrant decision tr...

Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies

Abstract In the event of a large-scale disaster, an important aspect of humanitarian logistics is the distribution of information or warnings to the affected population. This research develops the problem formulation and solution approach for a specific routing for relief problem, in which warnings should be disseminated to an affected community, using public announcement systems mounted on emergency vehicles. The problem statement is formulated to maximize the number of individuals of a community who are protected. An evolutionary algorithm framework is developed by coupling an agent-based model with a variable-length genetic algorithm to route emergency vehicles. The dynamics of interactions among consumers, emergency vehicles, and the spatiotemporal trajectory of the hazard are simulated using an agent-based modeling approach, and a variable-length genetic algorithm approach selects routes to warn a maximum number of consumers before they are affected by the emergency. The example that is explored in this research is contamination of a water distribution network. A fleet of emergency vehicles is equipped with public address systems and is deployed to warn consumers to stop using contaminated water. The framework is demonstrated for an illustrative virtual city, Mesopolis. The results of the evolutionary algorithm framework are compared with two conventional routing optimization approaches, including a covering tour problem approach and a manual routing approach, for four contamination scenarios. The evolutionary algorithm can be applied to route emergency service vehicles to broadcast information for other emergencies, such as flash flooding, hazardous materials incidents, and severe weather.

Complex Adaptive Systems Framework to Simulate the Performance of Hydrant Flushing Rules and Broadcasts during a Water Distribution System Contamination Event

AbstractIn the event that a contaminant is introduced to a water distribution system, utility managers must respond quickly to protect public health. Mitigation strategies specify response actions,...

Integrating an Agent-Based Model with a Multi-Objective Evolutionary Algorithm to Warn Consumers in a Water Contamination Event Using Emergency Vehicles

Many protective response actions are available to protect consumers affected by a water distribution contamination event. Routing a fleet of emergency vehicles to disseminate water warnings is considered in this study. Identifying optimal trips to effectively notice consumers is difficult as a water contamination event is a complex and dynamic system and vehicle routing problems are categorized as NP-hard domain. A novel framework is developed by coupling an agent-based model with an optimization algorithm to search for optimality in a warning dissemination. Solutions representing an optimal front are explored to demonstrate the relationship between the number of exposed consumers and the maximum travel time as conflicting objectives. NSGA-II is used with a tree-based representation. The developed framework is applied to a virtual case study, Mesopolis. INTRODUCTION Public health is threaten by toxins that are accidentally and intentionally introduced to a water network. Public trust in utility mangers can be eroded if actions to protect consumers are taken inappropriately. To avoid the loss of social trust in utility managers, decisions about protecting consumers should be made accordingly to mitigate the consequence of these events. The decision making process gives priority to a warning message dissemination process to inform consumers about the hazard associated with activities related to using tap water, such as drinking water. Utility managers have different choices to deliver a warning: broadcast a warning via media, route a fleet of emergency vehicles to use a siren as a warning sign, and deliver a leaflet at houses to warn and give instructions for short-term alternative water supply. To protect consumers effectively, the EPA (USEPA 2003) suggests locating the contaminant in the network before conducting response actions. When routing emergency vehicles, projecting a trip for each emergency vehicle is difficult because the characterization of a contaminant changes dynamically as more consumers become notified about the event. Notified consumers suspend the use of tap water for waterrelated activities that are perceived as a threat to their health. Also, utility managers may use containment strategies to remove the contaminant. The containment strategies directly change the hydraulics of a water network. Therefore, water distribution contamination events are defined as dynamic and complex systems. Using models with static demands to find the concentration of contamination at nodes may neglect important interactions. A sociotechnical model was proposed based on agent-based modeling (ABM) (Holland 1995) to evaluate the public health consequences of a water contamination event (Zechman 2011). The ABM approach models elements (agents) of a system and simulates interactions among the agents using a set of predefined rules to predict the emergent behavior of the system. The ABM model was extended 2550 World Environmental and Water Resources Congress 2013: Showcasing the Future

Integrating Genetic Programming and Agent-based Modeling to Identify Sensor-based Rules for Flushing Contaminated Water from a Pipe Network

A utility manager may become aware of a threat of contamination to a water distribution network through water quality sensor information, which may indicate that a biological pathogen or chemical contaminant was introduced to the network. In response, a utility manager can select a set of hydrants to flush contaminant from the network. As an event unfolds, a decision-maker may not be able to ascertain source characteristics, creating additional difficulties in determining the set of hydrants that should be opened. The research presented here develops a Genetic Programming (GP)-based approach to identify a set of response actions that are based on sensor information, instead of source characteristics, for guiding selection of hydrants. GP is a method within the class of evolutionary computation, and a solution is represented as a combination of values and symbols to represent a computer program for executing computations, such as a mathematical equation. GP is developed in this research to program a list of rules for opening and closing hydrants that will effectively protect public health for an ensemble of contamination events. An ensemble of contamination events is developed based on a set of similar activated sensors. As the public health effects of a contamination event are influenced by a set of complex interactions among consumers, utility operators, and the pipe network, an agent-based modeling framework is used to predict the dynamic location of a contaminant plume during a contamination event and the number of exposed consumers. To identify optimal hydrant strategies to flush a contaminant while considering the complexity of interactions in the system, a simulation-optimization model couples agent-based modeling with GP. Multiple contamination scenarios are modeled to evaluate potential solutions, and the simulation-optimization framework is demonstrated for a virtual mid-sized municipality, Mesopolis.

An Agent-based Modeling Framework for Assessing the Public Health Protection of Water Advisories

In the event that pathogens or toxins are introduced to a water distribution system, a utility manager may identify a threat through water quality data or alerts from public health officials. The utility manager may issue water advisories to warn consumers to reduce water use activities. As consumers react and change water demands, dynamic feedbacks among the community, utility managers, and the engineering infrastructure can create unexpected public health consequences and network hydraulics. A Complex Adaptive System (CAS)-based methodology is developed to couple an engineering model of a water distribution system with agent-based models (ABM) of consumers, public health officials, and utility managers to simulate feedback among management decisions, system hydraulics, and public behavior. A utility manager and a public health official are represented as agents, who respond to the event using a set of rules and equations that are based on a statistical analysis of a set of recorded water events. Consumers are represented as agents who update their water activities based on exposure to the contaminant and warnings from a utility agent and family members. A model of consumer compliance is developed using results from two surveys that report data to characterize consumer perceptions toward information sources during a water contamination event. The ABM framework is applied for an illustrative mid-sized virtual city to quantify the significance of interactions and advisories on public health consequences.

Sociotechnical simulation for evaluating adaptive threat response actions for water distribution contamination events

In the event that pathogens or toxins are introduced to a water distribution system, water utility managers should take the most effective actions to protect public health. As a contaminant propagates through the pipe network, a utility manager must select response actions based on available information, such as water quality sensing or complaints from consumers. Response plans are developed from a large set of options, including hydraulic responses that influence the mechanisms of system hydraulics and social responses that alter water consumption behaviors of the public through, for example, media broadcasts. The contaminant plume can shift from a previously expected direction due to public behaviors and altered system hydraulics during the event; in addition, new information will become available from water quality sensors and consumer complaints. Therefore, a manager should adapt to new conditions and information during the event to select the most effective responses. This research explores a new simulation framework to evaluate the efficiency of adaptive response rules for a water utility during a contamination event. A Complex Adaptive System (CAS)-based methodology is developed to couple the engineering model of a water distribution system with agent-based models of consumers and utility managers to simulate feedback among management decisions, system hydraulics, and the public behavior. A utility manager is represented as an agent, who responds to the event through a set of rules and equations, and consumers are represented as agents who update their water activities based on exposure to the contaminant and warnings from the utility agent. The proposed model is applied to an illustrative mid-sized virtual city to investigate the significance of interactions and identify sets of rules to effectively protect public health.