Recently, multimodal multiobjective optimization problems (MMOPs) have received
increasing attention. Their goal is to find a Pareto front and as many equivalent Pareto …

Different from multiobjective optimization problems (MOPs), multimodal MOPs (MMOPs)
focus on both decision and objective spaces rather than only objective one. Thus, finding a …

In this paper, the Hill Valley (HV) approach is applied to the drifting masses or agents in the
basic Gravitational Search Algorithm (GSA) for the path planning of humanoid robots. The …

In this paper we propose a specially designed memetic algorithm for multimodal
optimisation problems. The proposal uses a niching strategy, called region-based niching …

In this paper we present CBC (context based clearing), a procedure for solving the niching
problem. CBC is a clearing technique governed by the amount of heterogeneity in a …

The interest in multi-modal optimization methods is increasing in the recent years since
many of real-world optimization problems have multiple/many optima and decision makers …

Many evolutionary computational models have been introduced for solving engineering
optimization problems that usually intend to find the global optimum solution. These …

In the last few decades, identification of transition states has experienced significant growth
in research interests from various scientific communities. As per the transition states theory …

First order saddle points have important applications in different fields of science and
engineering. Some of their interesting applications include estimation of chemical reaction …

With enormous success in both science and engineering, the recent advances in
evolutionary computation—particularly memetic computing—is gaining increasing attention …