Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …

Over the past decade, surrogate-assisted evolutionary algorithms have demonstrated their
effectiveness across various computationally expensive real-world domains. Nevertheless …

Bayesian optimization is often used to optimize expensive black box optimization problems
with long simulation times. Typically Bayesian optimization algorithms propose one solution …

With the development of tourism, digital technology is increasingly being applied in the
design of tourist routes. This study takes into account that tourists are experience-driven in …

In engineering design optimization, it is common to encounter problems with multiple
objectives that need to be considered simultaneously [1]. A typical multiobjective …

The computational cost of modern simulation-based optimization tends to be prohibitive in
practice. Complex design problems often involve expensive constraints evaluated through …

Expensive objectives and constraints are key characteristics of real-world multi-objective
optimization problems. In practice, they often occur jointly with inexpensive objectives and …

The prediction of the statutory attained subdivision index is a challenging issue for the initial
design of ships due to the design freedom offered by a probabilistic damage stability …

Constrained many-objective optimization problems (CMaOPs) pose great challenges for
evolutionary algorithms to reach an appropriate trade-off of solution feasibility, convergence …

With the explosive growth of consumer electronic devices, edge computing has emerged as
a promising paradigm to process large-scale data in real-time and enhance data privacy …