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A multiobjective evolutionary algorithm toolbox for computer-aided multiobjective optimization.

K C Tan¹, T H Lee, D Khoo

¹Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 5, 2008

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This study introduces a user-friendly graphical tool for multiobjective optimization (MO) using evolutionary algorithms (MOEA). It efficiently finds optimal solutions without complex compromises, aiding decision-making in complex engineering problems.

Area of Science:

Computer Science
Engineering
Optimization

Background:

Multiobjective optimization (MO) problems involve multiple conflicting objectives.
Traditional methods often require aggregating objectives, losing valuable trade-off information.
Evolutionary algorithms offer a robust approach to MO.

Purpose of the Study:

To present an interactive graphical user interface (GUI) based multiobjective evolutionary algorithm (MOEA) toolbox.
To facilitate computer-aided multiobjective optimization without objective aggregation.
To support decision-making through features like goal settings and adaptive population sizing.

Main Methods:

Incorporation of Pareto's optimality to evolve nondominated solutions.
Development of a GUI-based toolbox with features for goal setting, constraint handling, and population management.

Related Experiment Videos

Utilization of adaptive niching for uniform solution distribution and convergence representation.

Main Results:

The toolbox effectively evolves families of nondominated solutions, distributing them uniformly along the trade-off front.
Demonstrated effectiveness through a distillation system design optimization problem.
Comparative performance analysis against established evolutionary MO optimization methods on benchmark problems.

Conclusions:

The developed MOEA toolbox provides an accessible and effective solution for computer-aided multiobjective optimization.
Its features enhance decision-making support and streamline the optimization process.
The toolbox is freely available, promoting wider adoption in research and practice.