DOA: a unary quality indicator for assessing the performance of many-objective optimization algorithm (MOOA).

Technical papers:

  • E. Dilettoso, S.A. Rizzo, and N. Salerno.(2017) A Weakly Pareto Compliant Quality Indicator. Mathemathical and Computational Applications 22 (1), 25. Open access: doi 10.3390/mca22010025PDF.
    Abstract
    In multi‐ and many‐objective optimization problems, the optimization target is to obtain a set of non‐dominated solutions close to the Pareto‐optimal front, well‐distributed, maximally extended and fully filled. Comparing solution sets is crucial in evaluating the performance of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. Therefore, an effective performance indicator must encompass these features as a whole and, above all, it must be Pareto dominance compliant. Unfortunately, some of the known indicators often fail to properly reflect the quality of a solution set or cost a lot to compute. This paper demonstrates that the Degree of Approximation (DOA) quality indicator is a weakly Pareto compliant unary indicator that gives a good estimation of the match between the approximated front and the Pareto‐optimal front.
    Keywords: multi‐objective  optimization;  many‐objective  optimization;  distance  indicator;  algorithms performance; Pareto optimality; quality indicator


  • E. Dilettoso, S.A. Rizzo, and N. Salerno.(2012) A new indicator to assess the quality of a Pareto approximation set applied to improve the optimization of a magnetic shield. Scientific Computing in Electrical Engineering (SCEE 2012), September 11-14, Zurich (CH). PDF.
    Abstract
    Evaluating the performances of an optimization algorithm is more complex in the case of multi-objective optimization problems than singleobjective ones. In the former case, the optimization aims to obtain a set of non-dominated solutions close to the Pareto-optimal front, well-distributed, maximally extended and full filled. This paper presents a new quality indicator encompassing the aforementioned goals. The quality indicator is then used to select a suitable algorithm for the multi-objective optimizationof a magnetic shield in an induction heating system. 

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