Parameters of the NO Experiment
The top part of the Network optimization experiment view
contains toolbar with following control elements:
Below the toolbar you can find a set of the experiment's parameters:
- Run. Click to
launch the experiment.
- Stop (active
only if the experiment is launched or paused) Click to stop the
parameters can be reset
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:
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
demand variation type
- specifies the type of acceptable demand deviation to consider during
- 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
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
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
- Optimization time limit
- sets the maximum time you would like to allot to defining one
- 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
specified percent of optimal (e.g. 5%, or 0.05 when specifying the MIP
- 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
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
- Number of threads
- the number of tasks that can be run in parallel.
- custom user-defined Java processor. If no custom pre-processor is
provided, the Default
pre-processor will be used.
- 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
current progress of the experiment:
- Optimization in
progress - the progress bar showing the current progress
of the experiment.
- Best solution
- the best current solution. If a better solution is found, it
will substitute the current table record.
- Solutions -
all the solutions that the experiment finds as it progresses.
- 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.
the NO experiment