Iterated local search (ILS) is a general and powerful metaheuristic which provides an easily
implementable way of improving the performance of local search algorithms. In this article …

Abstract The Building-Block Hypothesis appeals to the notion of problem decomposition and
the assembly of solutions from sub-solutions. Accordingly, there have been many varieties of …

The purpose of this paper is to investigate the use genetic algorithms (GAs) for solving the
Economic Lot Size Scheduling Problem (ELSP). The ELSP is formulated using the Basic …

In this paper, two types of fitness landscapes of the graph bipartitioning problem are
analyzed, and a memetic algorithm—a genetic algorithm incorporating local search—that …

Many problems of practical and theoretical importance within the fields of Artificial
Intelligence and Operations Research are of a combinatorial nature. Combinatorial …

NK-landscapes offer the ability to assess the performance of evolutionary algorithms on
problems with different degrees of epistasis. In this paper, we study the performance of six …

Genetic Algorithms (GAs) and evolutionary methods have been demonstrated to be flexible
and efficient optimization techniques with potential for locating global optima under general …

Evolutionary Algorithms are search algorithms based on the Darwinian metaphor of “Natural
Selection”. Typically these algorithms maintain a population of individual solutions, each of …

Epistasis measures have been developed for measuring statistical information about the
difficulty of a function to be optimized by a genetic algorithm (GA). We give first a review of …

It has been widely recognised in the computational intelligence and machine learning
communities that the key to understanding the behaviour of learning algorithms is to …