• Thunder cloud avoidance (Interactive MIRO demo)
    This application determines a flight path to avoid thunderclouds. The vertical extent of thunderclouds can be input as data, and a minimum cost flight path (under certain restrictions is determined (via a network flow formulation). This is implemented using GAMS/MIRO. Users can run the model on default data, view the results, then change data to generate a new scenario, comparing two saved scenarios in the comparison tool.
  • Bar Crawl Optimization Problem
    The objective of the Bar Crawl Optimization Problem is to select a set of bars and determine an ordering of them in such a way as to maximize the total benefit minus the total distance subject to a budget constraint.
  • Multiple Traveling Salesman Problem
    The Multiple Traveling Salesman Problem (mTSP) is a generalization of the Traveling Salesman Problem (TSP) in which more than one salesman is allowed. Given a set of cities, one depot where \(m\) salesmen are located, and a cost metric, the objective of the \(m\)TSP is to determine a tour for each salesman such that the total tour cost is minimized and that each city is visited exactly once by only one salesman.
  • Woodman's Grocery Delivery Problem
    This case study demonstrates how supermarkets can make use of ridesharing vehicles to augment their delivery fleet and how to develop a model that routes both the supermarkets vehicles and the ridesharing vehicles to satisfy customer demands. The problem can be modeled as a Heterogeneous Fleet Vehicle Routing Problem with Time Windows (HVRPTW).