Multi-Neighborhood Iterated Greedy (MNIG) algorithm, to solve the Fuzzy Multiproduct Multistage Scheduling Problem (FMMSP)

This is the MNIG algorithm written in Python to solve the FMMSP. The MNIG algorithm is implemented here as defined by the article: https://www.sciencedirect.com/science/article/abs/pii/S0950705120300344

The FMMSP model is defined in https://www.sciencedirect.com/science/article/abs/pii/S0925231220302563

This implementation is at least as good as the DBSA-LS algorithm to solve the FMMSP (as is confirmed using the only available public instance of the FMMSP, which is the one that comes by default inside this program).

Usage

python3 MNIG_to_FMMSP 5 1.1 4

This example command makes the algorithm run 250 iterations (which comes from $10*5^2$).

The meanings of the arguments are taken from the MNIG algorithm, they are $N$, $T_0$, and $d$, respectively.

Installation

Download the release and extract it. The command shown in Usage is executed in the same directory as the one that contains the extracted program.

Dependencies

You must have the following, already installed.

• The python3 interpreter.
• The Numpy module

Details about the code

The comments and the doc-strings are written in Spanish, because this project was originally created in Spanish.

An optional --debug flag can be passed to the program, to print each iteration with its sequence, the makespan of the sequence, and a few other info. At the end of the iterations, a table is printed with the starting times and the finish times of each job in the sequence, among other info.