A Novel Ranking Method Based on Subjective Probability Theory for Evolutionary Multiobjective Optimization

<table>The convergence curve in terms of the objective <svg height="14.475" id="M226" style="vertical-align:-3.13504pt" version="1.1" viewbox="0 0 14.8875 14.475" width="14.8875" xmlns="http://www.w3.org/2000/svg">
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<tspan style="font-size: 12.50px; " x="0" y="0">𝑓</tspan>
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<text transform="matrix(1,0,0,-1,-65.01,60.47)">
<tspan style="font-size: 8.75px; " x="0" y="0">1</tspan>
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</svg> (black) and <svg height="14.475" id="M227" style="vertical-align:-3.13504pt" version="1.1" viewbox="0 0 14.8875 14.475" width="14.8875" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,14.475)">
<g transform="translate(72,-60.42)">
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<tspan style="font-size: 12.50px; " x="0" y="0">𝑓</tspan>
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<tspan style="font-size: 8.75px; " x="0" y="0">2</tspan>
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</svg> (blue), respectively, when the proposed ranking method with the MOPSO is applied to the test function T4.</table>

Mathematical Problems in Engineering

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Figure 2

Figure 2: A Novel Ranking Method Based on Subjective Probability Theory for Evolutionary Multiobjective Optimization 