Work

A New Threshold Based Penalty Function Embedded MOEA/D

Year: 2016

Type: article

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.

Source: International Journal of Advanced Computer Science and Applications

DOI: 10.14569/ijacsa.2016.070281

Authors: Muhammad Asif, Nasser Mansoor, Rashida Adeeb, Wali Khan

Institutions: Kohat University of Science and Technology, King Khalid University, University of Peshawar

Language: English

Topic: Advanced Multi-Objective Optimization Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2315744420

FWCI: 0.827

Cites: 20

Cited by: 14

Related to: 10