EE6227: Programming Assignment
Programming Assignment
EE6227: Programming Assignment 1
This programming assignment offers some choices for the students. Most of the codes are available online.
The final submission must include the following:
1. Descriptions about at least two algorithms used in the study. In the case of single objective bound
constrained optimization, for example, basic differential evolution and an improved version can
be used. Alternatively, the basic PSO with momentum term and CLPSO (or HCLPSO) can be used.
With the algorithmic descriptions, the corresponding short code segments can be included. Codes
of CLPSO, HCLPSO and some other algorithms are available from
2. Total number of Fitness/objective function evaluations per run can be 50,000 for 10D (decision
variable) problems.
3. Descriptions about the important parameters of the chosen algorithms and how they were tuned.
Tuning experiments can be conducted using 5-10 repetitions, on 4-5 problems. ANOVA or iRace
may also be used for algorithmic parameter tuning.
4. After tuning the important parameters, final runs can be repeated 30 times.
5. 10 problems can be selected (out of 25+ benchmark problems) with 10 decision variables.
6. If a Real-world problem benchmark is used, 10 problems with 7 or more decision variables can be
selected. Selected problems can be briefly described in a few sentences.
7. Tables of results can include mean, median, standard deviation, convergence plots, etc.
8. Convergence plots show objective value (Y-axis in log scale) versus number of function evaluations
(X-axis linear scale).
9. Statistical testing can be conducted using Wilcoxon signed-rank test or another suitable test.