Over past few decades, as a powerful analytical tool to characterize the fitness landscape of
a problem, fitness landscape analysis (FLA) has been widely concerned and utilized for all …

Dynamic fitness landscape analyses contain different metrics to attempt to analyze
optimization problems. In this article, some of dynamic fitness landscape metrics are …

This paper investigates the influence of adaptive walks heuristics within local searches, by
studying to what extent a wiser choice among improving neighbors influences the expected …

Knapsack problems (KPs) are famous combinatorial optimization problems that can be
solved by evolutionary algorithms (EAs). In such methods, a key step is to produce new …

Fitness landscape analysis has been effectively used to analyze the characteristics of
combinatorial optimization problems (COPs) while investigating the behavior of applied …

Dynamic optimization problems (DOPs) have attracted increasing attention in recent years.
Analyzing the fitness landscape is essential to understand the characteristics of DOPs and …

For computationally hard discrete optimization problems, we rely on increasing computing
power to reduce the solution time. In recent years the computational capacity of the Graphics …

Teaching learning‐based optimization (TLBO) is a popular stochastic algorithm that has
recently been widely applied in a variety of optimization problems since its start. In TLBO …

To solve combinatorial optimization problems, many metaheuristics use first or best
improvement hill-climbing as intensification mechanism in order to find local optima. In …

In this paper, we propose new scenarios for simulating search operators whose behaviors
often change continuously during the search. In these scenarios, the performance of such …