A simultaneous EMO for the solution of the multi-Multi-Objective Optimization Problem

In this paper the recently introduced multi-Multi- Objective Optimization Problem (m-MOOP) is solved using a novel 'Simultaneous' approach. This is in contrast to both the 'Sequential' approach, which has been introduced previously and to a straightforward solution of the m-MOOP by posing it as a MOOP. The 'Simultaneous' approach is motivated by the need to overcome the apparent deficiencies of the other approaches. The simultaneous EMO algorithm, which is introduced in order to solve the m-MOOP, possesses several new EC related algorithmic features, including a multi- problem individual and a multi-problem sorting procedure. Formerly presented measures together with a newly introduced one, serve for a comparison between the introduced simultaneous approach with both the sequential approach and with a straightforward implementation of an EMO to an m- MOOP, which is posed as a MOOP. The comparison between the different approaches is practiced by using both academic examples as well as an engineering design example.