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  • Running up the wrong hill
    Running up the wrong hill
    Explore aspects of solver behaviour when solving non-linear optimization models
  • Portfolio optimization
    Portfolio optimization
    Allocate resources across a portfolio of choices, to maximize return and minimize risk
  • Facility location
    Facility location
    Locate facilities to minimize costs while meeting customer needs
  • Team selection
    Team selection
    Allocate team members in the best combination, given their skills and preferences
  • Optimal but not practical
    Optimal but not practical
    Learn how to address a common modelling issue: The solution is optimal, but not practical
  • We need more power: NEOS Server
    We need more power: NEOS Server
    Solve a model using the CPLEX solver via the NEOS Server
  • Python optimization Rosetta Stone
    Python optimization Rosetta Stone
    Implement a linear programming model in Pyomo, PuLP, OR Tools, Gekko, CVXPY, and SciPy
  • Logic conditions as constraints
    Logic conditions as constraints
    Convert logical implications into an equivalent set of optimization constraints
  • Product mix
    Product mix
    Find the best mix of products or ingredients
  • Well, that escalated quickly
    Well, that escalated quickly
    Five methods for deciding the best order for positioning devices in a rack