Performance evaluation of an evolutionary multiobjective optimization based area partitioning and allocation approach

Publication Type:
Conference Proceeding
IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 2018, 2018-July pp. 527 - 532
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AIM2018_EMObasedAPA_MH.pdfAccepted manuscript1.11 MB
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© 2018 IEEE. An Area Partitioning and Allocation (APA) approach was presented in[1]. The approach focused on optimizing the coverage performance of Autonomous Industrial Robots (AIRs) using multiple conflicting objectives and Voronoi partitioning. However, questions related to the optimality, convergence, and consistency of the Pareto solutions were not studied in details. In this paper, Inverted Generational Distance (IGD) metric is used to verify the convergence of the Pareto front towards Pareto optimal front (PF∗). The consistency in obtaining similar Pareto fronts for independent optimization runs is studied. The computational complexity of the approach with respect to the size of the coverage area and the number of AIRs is also discussed. Two application scenarios are used in this research.
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