TABLIX(1)						       Tablix User's Manual							 TABLIX(1)

NAME

tablix2 - general timetable solver

SYNOPSIS

tablix2 [ options ] file

DESCRIPTION

Tablix	is a powerful free software kernel for solving general timetabling problems. It uses a coarse-grained parallel genetic algorithm in combi-
nation with other techniques to construct sensible timetables from XML formatted problem descriptions. Tablix can run on a single host as well	as
on a heterogeneous parallel virtual machine using PVM3.

It  operates  by trying to assign variable resources to a number of events (sometimes called tuples) in a most efficient way. Various fitness mod-
ules can be specified in the problem description file to control the behaviour of the genetic algorithm.

Output is given in the form of a XML file. This file can be further processed by tablix2_output utility to export timetable data to  a	number	of
human  or  machine readable formats. Output XML file can also be used again as a problem description (input) file. In that case the previous solu-
tion will be used as a hint for Tablix when searching for a new solution.

OPTIONS

-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  popula-
 tion,	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.

-r
 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.

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

-d LEVEL
 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).

-h
 Shows a brief help message.

-v
 Shows compile time options, path to modules and copyright information.

-t MINUTES
 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.

-p PARAMETERS
 Set algorithm parameters. This is rarely used. The defaults should work fine in most cases. PARAMETERS is a comma  separated  string  of  parame-
 ter=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 min-
	       imum. 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  ini-
	       tialized  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.

-i PATH
 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.

USAGE

When you run tablix2 , you actually start the  master  process	that  will spawn the requested number of slave processes (kernels) on	the   vir-
tual machine. It will then multicast the configuration file to all the	nodes  and start listening for their reports.

You  can  press  Ctrl-C  (or  send  SIGINT)  to  stop  the  process. Tablix will save its state in a number of files  called  save?.txt  (it  will
prepend your prefix, if given). You can later resume the process  by  running Tablix with the -r parameter.

This feature will only	work if  you don't change the input XML file between saving and restoring  the	process. Changes to the number of  comput-
ing nodes (-n parameter) or to the physical configuration of the cluster are allowed however.

Tablix	will  save  population convergence information for each node during the computation into files with names conv?.txt. These files allow the
user to track the progress and sometimes predict the required time to find the solution to the given problem. Data in these files can  be  graphi-
cally represented with the tablix2_plot utility.

When  all  the	criteria  defined  by  the  fitness  modules  are  satisfied,  Tablix will output one XML  file  for each node (file names will be
result?.xml, prefix will be prepended if given).

NOTES

tablix2_kernel is executable for the slave process. It should not be started by hand, unless you know what your are doing (e.g. during debugging)

DIAGNOSTICS

Exit status is 0 if solutions were found, and 1 if the time limit was reached or the user has pressed Ctrl-C. Exit status is more  or  less  unde-
fined in case of errors during the execution (ideally it should be 2 in this case).

BUGS

Tablix will not notify the user if he or she is trying to create an impossible time table.

AUTHOR

Tomaz Solc (tomaz.solc@tablix.org)

SEE ALSO

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

Tomaz Solc							    2005-09-03								 TABLIX(1)