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Advanced Topics in Optimization

This document explores advanced optimization methods applied in civil engineering, focusing on critical areas such as water quality management, reservoir operations, water distribution systems, and transportation engineering. It discusses how optimization can address conflicting objectives among stakeholders, improve water quality, optimize resource allocation, and enhance operational efficiency. It highlights the roles of evolutionary algorithms and nonlinear models in solving complex optimization problems, providing a comprehensive overview of applications and methodologies in civil engineering contexts.

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Advanced Topics in Optimization

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  1. Advanced Topics in Optimization Applications in Civil Engineering Optimization Methods: M8L6

  2. Introduction Applications: • Water Quality Management: waste load allocation. • Reservoir Operation. • Water Distribution Systems • Transportation Engineering. Optimization Methods: M8L6

  3. Water Quality Management • Waste Load Allocation (WLA) in streams refers to the determination of required pollutant treatment levels at a set of point sources of pollution to ensure that water quality standards are maintained throughout the stream. • Stakeholders involved: Pollution Control Agency (PCA) and the dischargers (municipal and industrial) who are discharging waste into the stream • Goals/ Objectives: goals of the PCA are to improve the water quality throughout the stream whereas that of dischargers is to reduce the treatment cost of the pollutants • Optimization model with conflicting objectives Optimization Methods: M8L6

  4. Water Quality Management (Contd..) Maximization of water quality indicator (Dissolved Oxygen) Multi- Objective Minimization of fractional levels to pollutant to reduce treatment cost Water Quality Simulation Model: Nonlinear Suggested Readings: Tung and Hathhorn (1989), Sasikumar and Mujumdar (1998), and Mujumdar and Subbarao (2004) Evolutionary Algorithm can be used Optimization Methods: M8L6

  5. Reservoir Operation • In reservoir operation problems, to achieve the best possible performance of the system, decisions need to be taken on releases and storages over a period of time considering the variations in inflows and demands. • The goals can be: • Flood control • Hydropower generation • Meeting irrigation demand • Maintaining water quality downstream. Multiobjective in nature Optimization Methods: M8L6

  6. Reservoir Operation (Contd..) • Characterized by the uncertainty resulting from the random behavior of inflow and demand, incorporation of which in terms of risk may lead to a nonlinear optimization problem. • Application of evolutionary algorithms is a possible solution for such problems. • Suggested Readings: Jangareddy and Nagesh Kumar (2007), Nagesh Kumar and Janga Reddy (2007). Optimization Methods: M8L6

  7. Water Distribution Systems Objectives can be: • Meeting the household demands. • Minimizing cost of pipe system. • Meeting the required water pressure at all nodes of the distribution system. • Optimal positioning of valves. Multiobjective in nature Optimization Methods: M8L6

  8. Water Distribution Systems (Contd..) • Simulation model (e.g., Hardy Cross method): Nonlinear • Determination of optimum dosage of chlorine is also another important problem which is highly nonlinear because of nonlinear water quality simulation model. • Possible solution: Evolutionary Algorithm Optimization Methods: M8L6

  9. Transportation Engineering • Efficiently moving empty or laden containers for a logistic company or Truck and Trailer Vehicle Routing Problem (TTVRP). • Objectives: • Minimize routing distance • Minimize number of trucks • Model is nonlinear due to complicated inter relationship between the components. • Evolutionary Algorithm: Possible Solution. • Suggested Reading: Lee et al. (2003) Optimization Methods: M8L6

  10. Thank You Optimization Methods: M8L6

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