<p>Improvement process of the global optimal objective function value for the IABC.</p
<p>Progressive performance of genetic algorithm generations till optimum solution is achieved.</p
<p>Overlay of the optimization results after repeatedly running the IABC algorithm 10 times.</p
<p>Evolution of the objective/profit function <i>P</i>(<i>Q</i><sup>(<i>k</i>)</sup>) for all simula...
<p>The optimization processes of the optimal solution with different algorithms.</p
<p>The change of the value of the objective function as the number of evaluated solutions increases....
<p>Objective function’s values of the improved drawing algorithm when tuning PRmaxIterations paramet...
<p>Objective function’s values of the improved drawing algorithm when tuning accelerationPeriod para...
<p>Objective function’s values of the improved drawing algorithm when tuning accelerationRate parame...
<p>The objective functions and (floating solution form) versus iteration number for FISTA optimisa...
<p>Evolution of the misfit values of best available solution during the optimization framework execu...
<p>Objective function’s values of the improved drawing algorithm when tuning pathSqrSize parameter.<...
<p>Objective function’s values of the improved drawing algorithm when tuning refSize parameter.</p
<p>Objective function’s values of the improved drawing algorithm when tuning pathLength parameter.</...
<p>The performance improvement of function <i>propagat</i> using algorithm optimization.</p
International audienceThis paper deals with the convergence of the expected improvement algorithm, a...
<p>Progressive performance of genetic algorithm generations till optimum solution is achieved.</p
<p>Overlay of the optimization results after repeatedly running the IABC algorithm 10 times.</p
<p>Evolution of the objective/profit function <i>P</i>(<i>Q</i><sup>(<i>k</i>)</sup>) for all simula...
<p>The optimization processes of the optimal solution with different algorithms.</p
<p>The change of the value of the objective function as the number of evaluated solutions increases....
<p>Objective function’s values of the improved drawing algorithm when tuning PRmaxIterations paramet...
<p>Objective function’s values of the improved drawing algorithm when tuning accelerationPeriod para...
<p>Objective function’s values of the improved drawing algorithm when tuning accelerationRate parame...
<p>The objective functions and (floating solution form) versus iteration number for FISTA optimisa...
<p>Evolution of the misfit values of best available solution during the optimization framework execu...
<p>Objective function’s values of the improved drawing algorithm when tuning pathSqrSize parameter.<...
<p>Objective function’s values of the improved drawing algorithm when tuning refSize parameter.</p
<p>Objective function’s values of the improved drawing algorithm when tuning pathLength parameter.</...
<p>The performance improvement of function <i>propagat</i> using algorithm optimization.</p
International audienceThis paper deals with the convergence of the expected improvement algorithm, a...
<p>Progressive performance of genetic algorithm generations till optimum solution is achieved.</p
<p>Overlay of the optimization results after repeatedly running the IABC algorithm 10 times.</p
<p>Evolution of the objective/profit function <i>P</i>(<i>Q</i><sup>(<i>k</i>)</sup>) for all simula...
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