This paper will report results of various different metaheuristic search techniques applied to a complex student allocation problem. The problem has what might be considered a particularly difficult solution space when using the most natural definition of neighbourhood structure. The difficulty concerns the presence of many ”plateaux” large areas of solution space where all solutions have the s...

Mesh partitioning is an important problem that has extensive applications in many areas. Multilevel algorithms are a successful class of optimization techniques which addresses the mesh partitioning problem. In this paper we present an enhancement of the technique that uses nature inspired metaheuristic to achieve higher quality partitions. We apply and study a multilevel ant-colony (MACO) opti...

The scarcity of radio channel is the main bottleneck in the enhancement of system capacity while maintaining quality of service in mobile cellular networks. A channel allocation scheme which can adapt the varying load of a network may help to overcome that bottleneck to some extent. Thus, dynamic channel allocation (DCA) is an important problem in the mobile cellular networks. In this paper, we...

This paper presents an object-oriented software system that implements a cuckoo search (CS) metaheuristic for unconstrained optimization problems. Yang and Deb developed cuckoo search algorithm in MATLAB and tested it on some standard benchmark functions as well as on some engineering optimization problems where it showed promising results. We developed our algorithm in JAVA programming languag...

This paper was written to accompany the author’s keynote talk for the Workshop on Computational Science in Software Engineering held in conjunction with International Conference in Computational Science 2006 in Reading, UK. The paper explains how software engineering activities can be viewed as a search for solutions that balance many competing constraints to achieve an optimal or near optimal ...

using advanced techniques of econometrics and a metaheuristic optimization approach, this study attempts to evaluate the potential advantages of international portfolio diversification for east asian international investors when investing in the middle eastern emerging markets. overall, the results of both econometric and the metaheuristic optimization methods are supporting each other. finding...

Given the NP-Hard nature of many optimization problems, it is often impractical to obtain optimal solutions to large-scale problems in reasonable computing time. For this reason, heuristic and metaheuristic search approaches are used to obtain good solutions fast. However, these techniques often struggle to develop a good balance between local and global search. In this paper we propose a hybri...

This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the dis...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a com...