Visualizing and analyzing multiple Pareto-optimal solutions obtained using an evolutionary
multi-or many-objective optimization algorithm is as important a task as the task of finding …

The incoordination between public transportation system construction and urban
infrastructure development is a challenge for the sustainable development of cities …

In evolutionary many-objective optimization, diversity maintenance plays an important role in
pushing the population towards the Pareto optimal front. Existing many-objective …

Multiobjective evolutionary algorithms (MOEAs) effectively solve several complex
optimization problems with two or three objectives. However, when they are applied to many …

Industrial symbiosis is a promising approach for energy conservation and emission
reduction in the global industrial sector. The objective of this research is to optimize …

To represent a many-objective Pareto-optimal front having four or more dimensions of the
objective space, a large number of points are necessary. However, for choosing a single …

Machine learning models are deployed as a central component in decision making and
policy operations with direct impact on individuals' lives. In order to act ethically and comply …

One of the crucial challenges of solving many-objective optimization problems is uniformly
well covering of the Pareto-front (PF). However, many the state-of-the-art optimization …

Traditionally, the High‐Level Synthesis (HLS) for Field Programmable Gate Array (FPGA)
devices is a methodology that transforms a behavioral description, as the timing …

Identifying regions of interest (RoI) in the design space is extremely useful while building
metamodels with limited computational budget. Self-organizing maps (SOM) are used as a …