Abstract: Recently, we proposed a new threshold based penalty function. The threshold dynamically controls the penalty to infeasible solutions. This paper implants the two different forms of the proposed penalty function in the multiobjective evo-lutionary algorithm based on decomposition (MOEA/D) frame-work to solve constrained multiobjective optimization problems. This led to a new algorithm, denoted by CMOEA/D-DE-ATP. The performance of CMOEA/D-DE-ATP is tested on hard CF-series test instances in terms of the values of IGD-metric and SC-metric. The experimental results are compared with the three best performers of CEC 2009 MOEA competition. Experimental results show that the proposed penalty function is very promising, and it works well in the MOEA/D framework.

Muhammad Asif Jan, Nasser Mansoor Tairan, Rashida Adeeb Khanum and Wali Khan Mashwani, “A New Threshold Based Penalty Function Embedded MOEA/D” International Journal of Advanced Computer Science and Applications(IJACSA), 7(2), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070281

@article{Jan2016,
title = {A New Threshold Based Penalty Function Embedded MOEA/D},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070281},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070281},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {2},
author = {Muhammad Asif Jan and Nasser Mansoor Tairan and Rashida Adeeb Khanum and Wali Khan Mashwani}
}