Previous researchers have made impressive strides in develo** algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

The simulation-driven metaheuristic algorithms have been successful in solving numerous
problems compared to their deterministic counterparts. Despite this advantage, the …

Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly
growing area of investigation. EDMO employs evolutionary approaches to handle multi …

Recommender systems have been widely applied to several domains and applications to
assist decision making by recommending items tailored to user preferences. One of the …

Evolutionary algorithms (EAs) have shown to be promising in solving many-objective
optimization problems (MaOPs), where the performance of these algorithms heavily …

In many-objective optimization problems (MaOPs), forming sound tradeoffs between
convergence and diversity for the environmental selection of evolutionary algorithms is a …

Multi-objective optimization has been adopted in many engineering problems where a set of
requirements must be met to generate successful applications. Among them, there are the …

The uncertainty involved in the interpreted geological model may be categorized as the
stratigraphic uncertainty and the properties uncertainty. Note that although the influence of …

As verified structures for landslide mitigation, stabilizing piles are often adopted to treat local
failure zones of width-limited soil slopes. To achieve a balance between slope safety and …

In real life, there are many dynamic multi-objective optimization problems which vary over
time, requiring an optimization algorithm to track the movement of the Pareto front (Pareto …