Firefly algorithm (FA) is a metaheuristic for global optimization. In this paper, we address the practical testing of a heuristic-based FA (HBFA) for computing optima of discrete nonlinear optimization problems, where the discrete variables are of binary type. An important issue in FA is the formulation of attractiveness of each firefly which in turn affects its movement in the search space. Dy...

We introduce a new interval global optimization method for solving bound constrained problems. The method originates from a small standalone software and is implemented in the COCONUT Environment, a framework designed for the development of complex algorithms, containing numerous state-of-the-art methods in a common software platform. The original algorithm is enhanced by various new methods im...

The weighted CSP framework is a soft constraint framework with a wide range of applications. Most current state-of-the-art complete solvers can be described as a basic depth-first branch and bound search that maintain some form of arc consistency during the search. In this paper we introduce a new stronger form of arc consistency, that we call existential directional arc consistency and we prov...

Consistency techniques proved to be an efficient method for reducing the search space of CSP. Several consistency techniques were proposed for soft constraint frameworks too. In this paper, we propose a full arc consistency (FAC) for weighted CSP (WCSP) and an algorithm for enforcing FAC and maintaining it during Branch & Bound search. We also define the transformation of constraint hierarchies...

Constraint Optimization problems are commonly solved using a Branch and Bound algorithm enhanced by consistency maintenance procedures (Wallace and Freuder 1993; Larrosa and Meseguer 1996; Larrosa et al. 1999; Larrosa and Schiex 2003; 2004). All these algorithms traverse the search space in a chronological order and gain their efficiency from the quality of the consistency maintenance procedure...

We give a pattern search method for nonlinearly constrained optimization that is an adaption of a bound constrained augmented Lagrangian method first proposed by Conn, Gould, and Toint [SIAM J. Numer. Anal., 28 (1991), pp. 545–572]. In the pattern search adaptation, we solve the bound constrained subproblem approximately using a pattern search method. The stopping criterion proposed by Conn, Go...

The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promis...

Real-life problems present several kinds of preferences. We focus on problems with both positive and negative preferences, that we call bipolar preference problems. Although seemingly specular notions, these two kinds of preferences should be dealt with differently to obtain the desired natural behaviour. We technically address this by generalizing the soft constraint formalism, which is able t...

Recently, a general definition of arc consistency (AC) for soft constraint frameworks has been proposed [1]. In this paper we specialize this definition to weighted CSP and introduce two O(ed3) enforcing algorithms. Then, we refine the definition and introduce a stronger form of arc consistency (AC*) along with two O(n2d2 + ed3) algorithms. As in the CSP case, an important application of AC is ...