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Settings of the NO Experiment

If the Experiment settings window is not open, click in the experiments controls.

Network optimization experiment considers all periods specified in the Periods table. The starting date of the experiment corresponds to the date specified in the Start column of the first period (in the Periods table), and the ending date corresponds to the date specified in the End column of the last period (in the Periods table).

Experiment settings:

  • Ignore straight routes — [use it only if Straight is disabled in the Paths table] defines if the experiment considers straight routes or ignores them.

    By straight routes in this case we mean the actual routes (roads) that are treated as straight routes because their data couldn't be obtained (e.g. the road does not exist, the data on this route failed to download, etc.). Hence, a straight line connecting two objects. This parameter defines if the experiment should consider such straight routes.

  • Select demand variation type — specifies the type of acceptable demand deviation to consider during the experiment:
    • Exact demand — [selected by default] — no deviation is allowed. The down and up penalties will be applied instantly on violating the specified demand.
    • 100% — 105% — deviation of up to 5% is allowed. The up penalty will be applied only if the violation exceeds the 5% threshold.
    • 95% — 100% — deviation of up to — 5% is allowed. The down penalty will be applied only if the violation is below the — 5% threshold.
  • Select search type for N best solutions — defines the objective of the experiment run. You may find the number of solutions satisfying 1 site as well a number of sites.
    • Find N best — allows you to define the number of best solutions for the optimal number of sites. Having found the best solution, the solver blocks it, excludes its flows, and starts searching again for the second best solution. The solver continues searching until the required number of best solutions is found. In other words, the solver solves a number of separate tasks and provides the best result for each of them.
    • Solution pool — allows you to define multiple solutions to a mixed integer programming (MIP). The solver will find the required number of best solutions during a single search and return all of the possible solutions.
  • Number of best solutions to find — specify the number of solutions that you need to find.
  • Optimization time limit — sets the maximum time you would like to allot to defining one solution.
  • Relative MIP gap — sets a relative tolerance on the gap between the best found solution and the best possible solution. The solver will stop as soon as it finds the solution within the specified percent (e.g. 5%, or 0.05 when specifying the MIP gap).
  • Number of threads to use — the number of tasks that can be run in parallel.
  • Problem definition type — define what to formulate the site selection problem (sites with the Consider inclusion type) for the solver with:
    • Use Big M — [selected by default] it is a big enough constraint used in a mixed integer programming (MIP) to model if...then. If its value is too big, result might be inaccurate (e.g. the second and the third best results are better than the first one).
    • Indicator — use it if the results acquired using Big M are inaccurate.
  • Finances stats unit — the monetary unit that will be used in the statistics.
  • Product stats unit — the product measurement unit (also includes units defined in the Measurement Units table), in which the Flows Amount on the Optimization results page will be displayed.
  • Distance stats unit — the distance measurement unit that will be used in the statistics.
  • Optimizer log view — [available only during the experiment run] the log view shows the current progress of the experiment:
    1. Best solution — the best current solution. If a better solution is found, it will substitute the current table record.
    2. Iterations — all the solutions that the experiment finds as it progresses.
    3. Optimization in progress — the progress bar showing the current progress of the experiment.

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