The cost of software testing could be reduced if faulty entities were identified prior to the
testing phase, which is possible with software fault prediction (SFP). In most SFP models …

This paper provides an overview of developments on termination conditions in evolutionary
algorithms (EAs). It seeks to give a representative picture of the termination conditions in …

Finding good solutions on multi-modal optimization problems depends mainly on the
efficacy of exploration. However, many search techniques applied to multi-modal problems …

A multi-modal search space can be defined as having multiple attraction basins–each basin
has a single local optimum which is reached from all points in that basin when greedy local …

This paper reports results from experiments using differential evolution (DE) in a high-fidelity
simulation model of a contemporary financial market in which various traders are each …

Minimum Population Search is a recently developed metaheuristic specifically designed to
optimize high dimensional multi-modal functions. In this paper, Minimum Population Search …

When optimizing multi-modal spaces, effective search techniques must carefully balance
two conflicting tasks: exploration and exploitation. The first refers to the process of identifying …

Differential evolution (de) is a popular population-based meta-heuristic that has been
successfully used in complex optimization problems. Premature convergence is one of the …

Population-based heuristics can be effective at optimizing difficult multi-modal problems.
However, population size has to be selected correctly to achieve the best results. Searching …

Optimization in multi-modal search spaces requires both exploration and exploitation. The
role of exploration is to find promising attraction basins, and the role of exploitation is to find …