This is an example on how an readme file can look, see this file for info about how to contribute.
The paper consider 10 instances for the classical bi-objective linear assignment problem.
To cite the paper use
@ARTICLE{Pedersen08,
Author = {Pedersen, C.R. and Nielsen, L.R. and Andersen, K.A.},
Title = {The Bicriterion Multi Modal Assignment Problem: Introduction, Analysis, and Experimental Results},
Year = {2008},
Volume = {20},
Number = {3},
Journal = {Informs Journal on Computing},
Institution = {Department of Operations Research, University of Aarhus},
School = {Department of Operations Research, University of Aarhus},
Pages = {400–-411},
Doi = {10.1287/ijoc.1070.0253}
}
To cite this repository use
@Electronic{MOrepo-Pedersen08,
Title = {Bicriterion assignment and multi modal assignment problems (MOrepo-Pedersen08)},
Author = {Pedersen, C.R. and Nielsen, L.R.},
Url = {https://github.com/MCDMSociety/MOrepo-Pedersen08},
Year = {2008},
Note = {Instance and result files at MOrepo.}
}
To cite the Multi-Objective Optimization Repository use
@Electronic{MOrepo,
Title = {Multi-Objective Optimization Repository (MOrepo)},
Author = {L. R. Nielsen},
Url = {https://github.com/MCDMSociety/MOrepo},
Year = {2017},
}
In a paper (written using LaTeX) you may write:
Instances from \cite{Pedersen} are tested which are available from the Multi-Objective
Optimization Repository (MOrepo) (\cite{MOrepo, MOrepo-Pedersen08}).
Always remember to cite the research paper and not the repository if you don't want to include all citations.
Instances are named Template_AP_n<n>.<raw/xml>
where n
is the size of the problem. The paper considers
instances of size 5-50; however, the instance set also contains 5 instances of size 60-100. Costs
are generated random in [0,30].
All instance files are given in both xml and raw format. The xml format is self explainable (see e.g. ex1).
We use the following parameter names:
-
$n$ = dimension/size -
$c^{k}_{r,c}$ =$k$ 'th cost of assigning row$r$ to column$c$ .
The instances have the following format:
n
c^{0}_{0,0}... c^{0}_{0,n-1}
c^{0}_{1,0}... c^{0}_{1,n-1}
...
c^{0}_{n-1,0}... c^{0}_{n-1,n-1}
c^{1}_{0,0}... c^{1}_{0,n-1}
c^{1}_{1,0}... c^{1}_{1,n-1}
...
c^{1}_{n-1,0}... c^{1}_{n-1,n-1}
That is, first the dimension, then the costs for the first criterion and next the cost for the second criterion.
The instances are contained in the sub folder MMAP
. Instances are named
Template_MMAP_d<n>_e<I1>_c<I2>_m<M>_s<S>_<Y>.xml
where Y
is the instance number of a BiMMAP of
size I1
and cost range I2
using method M
and shape S
.
A total of 8000 instances are provided. That is, 100 instances of each of the following 80 possible configurations were generated:
- n: 4, 6, 8, 10.
- I1: 2-8 (not for method 2) and 10-30.
- I2: 0-500 and 0-10000.
- (M,S): (1, −60), (1,0), (1, 60), (2, 3), (2, 4), (3, 0).
Restults are given in the results
folder using the json
format (see Step 3).