In the past, the notion of fitness landscapes has found widespread adoption. Many different
methods have been developed that provide a general and abstract framework applicable to …

Discovering the conditions under which an optimization algorithm or search heuristic will
succeed or fail is critical for understanding the strengths and weaknesses of different …

Teaching–Learning-Based Optimization (TLBO) seems to be a rising star from amongst a
number of metaheuristics with relatively competitive performances. It is reported that it …

The steady supply of new optimization methods makes the algorithm selection problem
(ASP) an increasingly pressing and challenging task, specially for real-world black-box …

Algorithm selection and configuration is a challenging problem in the continuous
optimization domain. An approach to tackle this problem is to develop a model that links …

The performance of optimization algorithms, including those based on swarm intelligence,
depends on the values assigned to their parameters. To obtain high performance, these …

Traditional inversion method is the most commonly used procedure for three-dimensional
(3D) resistivity inversion, which usually takes the linearization of the problem and …

I present a new approach to evolutionary search called novelty search, wherein only
behavioral novelty is rewarded, thereby abstracting evolution as a search for novel forms …

The fitness landscape of the no-wait (continuous) flow-shop scheduling problem is
investigated by examining the ruggedness of the landscape and the correlation between the …

We show that given a k-bounded pseudo-Boolean function f, one can always compute the
cth moment of f over regions of arbitrary radius in Hamming space in polynomial time using …