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> tablix2_plot(1)
> tablix2_benchmark(1)
> tablix2_test(1)
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tablix2 [ options ] file


(sometimes called tuples) in a most efficient way. Various fitness modules can by tablix2_output utility to export timetable data to a number of human or


-N N

Start N slave processes (kernels). This is the number of spawned PVM3 tasks on the virtual machine. A larger number means larger total population, steeper convergence graph, more exhaustive search for solutions and a smaller chance of premature convergence. However, optimal number depends on the number and speed of computing nodes. For a virtual machine composed of reasonably fast machines start with N = 4 * i where i is the number of computing nodes. Tablix will try to arrange tasks so that all computing nodes will have equal load. (Be sure to set speed field correctly in your PVM3 hostfile). Default is 4.
-L N
When a population in a slave process (computing node) reaches a local minimum that process will try to execute an algorithm called local search. This is a way to nudge the main genetic algorithm out of a local minimum trap if it gets caught in it. However it is usually not efficient for this algorithm to run simultaneously on many nodes. This option sets the number of computing nodes that are allowed to simultaneously perform local search. Setting N to 0 disables local search and -1 means no limit. Default is 1.
Restore saved populations instead of starting with random ones. Populations are loaded from a number of PREFIXsave?.txt files, where PREFIX is the prefix, specified with the -o option. See below.


Specify a prefix for output files. All output files (result, saved populations and convergence graph info) will have PREFIX prepended.


Set the verbosity level, where LEVEL is one of the following: 0 (only fatal error messages are shown), 1 (fatal and non-fatal errors), 2 (errors and a progress indicator), 3 (all of the above plus some informational messages) or 4 (all of the above plus debug messages).


Shows a brief help message.


Shows compile time options, path to modules and copyright information.
Sets a time limit for the genetic algorithm. Tablix will stop if no solution is found after set number of minutes. The effect is same as when Ctrl-C is pressed. Setting MINUTES to 0 disables this feature. Default is disabled. Use this option to prevent Tablix to run indefinitely if there is no possible solution.
Set algorithm parameters. This is rarely used. The defaults should work fine in most cases. PARAMETERS is a comma separated string of parameter=value pairs. Following parameters are available: popsize Population size of one node in cluster. Bigger populations mean less generations per minute but also in some cases more optimized results. Default 500. toursize Tournament size. Bigger tournament sizes result in faster convergence, which can result in finding a local instead of a global minimum. Default 3. mutatepart What part of the population will mutate each generation. 2 means one half, 3 means one third, etc. More mutations usually result in slower convergence but can help to avoid local minimums. Default 4. randpart What part of the population will be randomized each generation. Randomizations have the same effect as mutations. Default 6. maxequal How many equally graded timetables can exist at the same time in a population. Smaller values result in slower convergence but can help to avoid local minimums. Default 20. finish Tablix will finish when the number of all mandatory errors in the best solution reaches zero and this best solution had the same fitness value for N sequential populations. This option enables you to set the value of N. It has no effect if there are no non-mandatory errors defined (in that case Tablix finishes as soon as the number of all mandatory errors reaches zero). Default 300. migrtime How often do parts of populations migrate between nodes. Smaller value means more migrations, which results in faster convergence. Default 40. migrpart What part of population will migrate between nodes. Default 10. localtresh How many equally graded populations to wait before starting local search (if enabled). Default 100. localstep Initial step for the local search algorithm. Larger values mean more exhaustive and slower search. Default 4. pophint If the user has loaded an XML file that already contains a partial or a full solution, then a part of the population can be initialized with this solution. This parameter defines the percentage of the timetables in the population that will be initialized (other timetables will be initialized with random values). Values must be between 0 and 100. Larger values mean that the solution given in the XML file will have a greater possibility of being included in the final solution. If there is no solution in the XML file then this parameter has no effect. Default 25. cachesize This is the maximum number of timetable fitness values that will be held in the fitness cache. Larger values mean more cache search overhead but may improve cache hit/miss ratio. It is probably unwise to use caches larger than 32. In general fitness caching will reduce performance at the start of the genetic algorithm and improve it at the end. Set to 0 to turn off caching. Default 16.


Sets the path to fitness modules. By default the module path is set to the location where fitness modules were installed by make install command.


When you run tablix2 , you actually start the master process that will (-n parameter) or to the physical configuration of the cluster are allowed however. represented with the tablix2_plot utility.


tablix2_kernel is executable for the slave process. It should not be started




pvm(1PVM), pvmd(1PVM), tablix2_output(1), tablix2_plot(1), tablix2_benchmark(1), tablix2_test(1), Tablix User's Manual, Tablix modules HOWTO TABLIX2(1)

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