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 …

Measuring the performance of an algorithm for solving multiobjective optimization problem
has always been challenging simply due to two conflicting goals, ie, convergence and …

Recently, multi-objective evolutionary algorithms (MOEAs) have been widely explored and
applied to many real-world problems. Particularly, preference-based MOEAs are among the …

There are some real-world problems in which multiple objectives conflict with each other
and the objectives change with time. These problems require an optimization algorithm to …

This paper introduces a novel hybrid optimization algorithm called MoSSE by combining the
features of Multi-objective Spotted Hyena Optimizer (MOSHO), Salp Swarm Algorithm (SSA) …

In the present work, a new digital design system, GenYacht, is proposed for the creation of
optimal and user-centred yacht hull forms. GenYacht is a hybrid system involving generative …

This paper aims to analyze Iran's long-term power sector development from economic,
environmental, social, and sustainable perspectives. For this purpose, a linear programming …

It is generally accepted that conflicts between convergence and distribution deteriorate with
an increase in the number of objectives. Furthermore, Pareto dominance loses its …

In preference-based optimization, knee points are considered the naturally preferred tradeoff
solutions, especially when the decision maker has little a priori knowledge about the …

In multiobjective optimization, it is nontrivial for decision makers to articulate preferences
without a priori knowledge, which is particularly true when the number of objectives …