Parameters of the NO Experiment

The top part of the Network optimization experiment view contains toolbar with following control elements:

Run. Click to launch the experiment.
Stop (active only if the experiment is launched or paused) Click to stop the experiment.

Below the toolbar you can find a set of the experiment's parameters:

Note: The experiment parameters can be reset to their default values if required.

Experiment duration - the period of time that will be processed by the experiment. Network optimization experiment considers all periods specified in the Periods table. The actual experiment duration is specified below the parameter as Start date and End date:

Note: 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).
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 soluitions - 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. In other words, it solves the problem just once returning all 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 integer objective and the objective of the best node remaining. The solver will stop as soon as it finds the solution within the specified percent of optimal (e.g. 5%, or 0.05 when specifying the MIP gap).
Problem definition type - define what to formulate the problem for the solver with:
- Big M - [selected by default] it is a big enought 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 results acquired using Big M are inaccurate.
Number of threads - the number of tasks that can be run in parallel.
Pre-processor - custom user-defined Java processor. If no custom pre-processor is provided, the Default pre-processor will be used.
Post-processor - custom user-defined Java processor. If no custom post-processor is provided, the Default post-processor will be used.
Optimizer log view - [available only during the experiment run] the log view shows the current progress of the experiment:
1. Optimization in progress - the progress bar showing the current progress of the experiment.
2. Best solution - the best current solution. If a better solution is found, it will substitute the current table record.
3. Solutions - all the solutions that the experiment finds as it progresses.
4. Experiment log - the log of experiment execution. This data can be also found in the ALX log file if you choose Help -> Show log file.