Ontology alignment is an essential and complex task to integrate heterogeneous ontology. The meta-heuristic algorithm has proven be effective method for ontology alignment. However, it only applies the inherent advantages of meta-heuristics rarely considers execution efficiency, especially multi-objective model. performance such optimization models mostly depends on well-distributed fast-conver...

We describe three experiments using meta-language and meta-reasoning to solve problems involving belief, heuristics, and points of view. These experiments use the knowledge representation system SPHERE, built at Hewlett-Packard Laboratories and based on the ideas of FOL [20]. A key idea underlying our research is the segmentation of knowledge into contexts and the meta-linguistic treatment of t...

In this paper we prove that in some practical situations, there is a free lunch for hyper-heuristics, i.e., for search algorithms that search the space of solvers, searchers, meta-heuristics and heuristics for problems. This has consequences for the use of genetic programming as a method to discover new search algorithms and, more generally, problem solvers. Furthermore, it has also rather impo...

This study presents shape optimization of a gravity dam imposing stability and principal stress constraints. A gravity dam is a large scale hydraulic structure consisting of huge amount of concrete material. Hence, an optimum design gives a cost-benefit structure due to the fact that small changes in shape of dam cross-section leads to large saving of concrete volume. T...

The hybridization of population-based meta-heuristics and local search strategies is an effective algorithmic proposal for solving complex continuous optimization problems. Such hybridization becomes much more effective when the local search heuristics are applied in the most promising areas of the solution space. This paper presents a hybrid method based on Clustering Search (CS) to solve cont...

Many hard optimization problems can only be effectively handled by meta-heuristic methods. Some continuous optimization problems have specifi c characteristics that demand a particular interest. These features include the location of the optima in a specifi c region of search space. Hence the main goal of this paper is assessing the performance of some outstanding population-based meta-heuristi...

The work presented in this paper could be thought of as a case based hyper-heuristic approach for examination timetabling problems. A hyper-heuristic can be taken to be an automated approach to choose heuristics. Heuristics and meta-heuristics are employed in this capacity in [1] and [2]. In this paper the case-based paradigm is explored as a heuristic selector for examination timetabling probl...

With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Co...