MOFEPSO: Multi-objective feasibility enhanced particle swarm

A multi-objective constrained optimizer capable of handling highly constrained problems.
Updated 5 Oct 2018

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Multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) is an enhanced particle swarm optimization (PSO) approach that utilizes a Pareto dominance technique. MOFEPSO is a constrained multi-objective optimizer designed to handle highly-constrained optimization problems. The technique treats feasible and infeasible particles differently. Infeasible particles do not need to evaluate objective functions and fly only based on social attraction depending on a single violated constraint, called the activated constraint (AC), which is selected in each iteration based on constraint priorities and flight occurs only along dimensions of the search space to which the AC is sensitive. To ensure progressive improvement of constraint satisfaction, particles are not allowed to violate a satisfied constraint in MOFEPSO. Although MOFEPSO does not require any feasible solutions in the initialized swarm, it requires at least one particle satisfying each constraint.

Mehmet Sinan Hasanoglu and Melik Dolen. "Multi-objective feasibility enhanced particle swarm optimization". In: Engineering Optimization 50.12 (Feb. 2018), pp. 2013-2037.

Cite As

Mehmet Sinan Hasanoglu (2024). MOFEPSO: Multi-objective feasibility enhanced particle swarm (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
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Version Published Release Notes

Added support for handling unconstrained problems.


Cleaned up files


Examples added