This paper provides a survey of the most important repair heuristics used in evolutionary
algorithms to solve constrained optimization problems. Popular techniques are reviewed …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

Web services are rapidly changing the landscape of software engineering. One of the most
interesting challenges introduced by web services is represented by Quality Of Service …

In this paper, we propose a generic, two-phase framework for solving constrained
optimization problems using genetic algorithms. In the first phase of the algorithm, the …

Constraint satisfaction problem (CSP) is defined as a set of variables whose values need to
satisfies a set of constraints. Ant colony optimization (ACO) has been proved to be a …

The main aim of this paper is the imposition of constraints for the multiobjective optimizations
of magnetic gears. In order to reduce the computational effort, a semianalytic design …

The method of handling infeasible solutions in an evolutionary search algorithm [eg, genetic
algorithms (GAs)] is crucial to the effectiveness of the solution search process. This problem …

Experimental data from neuroscience suggest that a substantial amount of knowledge is
stored in the brain in the form of probability distributions over network states and trajectories …

The ability of ant colonies to form paths for carrying food is rather fascinating. When
considering the scale of ants, this path-finding problem is complex: ants only have a local …