Supported by IEEE CIS ISATC Task Force on Transfer Learning and Transfer Optimization
In multiobjective optimization problems, there may exist two or more distinct Pareto optimal sets
(PSs) corresponding to the same Pareto Front (PF). These problems are defined as multimodal
multiobjective optimization problems (MMOPs). Arguably, finding one of these multiple PSs may be
sufficient to obtain an acceptable solution for some problems. However, failing to identify more
than one of the PSs may prevent the decision maker from considering solution options that could
bring about improved performance.
The aim of this special session is to promote the research on MMO and hence motivate researchers to formulate real-world practical problems. Given that the study of multimodal multiobjective optimization (MMO) is still in its emerging stages, although many real-word applications are likely to be amenable to treatment as a MMOP, to date the researchers have ignored such formulations:
This special session is devoted to the novel approaches, algorithms and techniques for solving MMOPs. The main topics of the special session are:
Papers should be submitted following the instructions at the IEEE CEC 2019 web site. Please select the main research topic as the Special Session on “multimodal multiobjective optimization”. Accepted papers will be included and published in the conference proceedings.
7th Jan 2019, 23:59 (GMT)