The ultimate goal of semantic web (SW) is to implement mutual collaborations among ontology-based intelligent systems. To this end, it necessary integrate those domain-independent and cross-domain ontologies by finding the correspondences between their entities, which so-called ontology matching. improve quality alignment, in work, matching problem first defined as a sparse multi-objective opti...

In high-dimensional space, most multi-objective optimization algorithms encounter difficulties in solving many-objective problems because they cannot balance convergence and diversity. As the number of objectives increases, non-dominated solutions become difficult to distinguish while challenging assessment diversity objective space. To reduce selection pressure improve diversity, this article ...

In the field of many-objective evolutionary optimization algorithms (MaOEAs), how to maintain balance between convergence and diversity has been a significant research problem. With increase number objectives, mutually nondominated solutions increases rapidly, multi-objective algorithms, based on Pareto-dominated relations, become invalid because loss selection pressure in environmental selecti...

This paper gives a concise introduction to Multi-Objective Genetic Algorithms and FPGAs and it reveals that how Automatic Test Pattern Generation method can be formulated in terms of CNF form which in turn used to generate test patterns using Multi-Objective Genetic Algorithm. By applying a Multi-Objective Genetic Algorithm on this CNF form, it has been observed from the experiments that as the...

In this paper, based on Magnetotactic Bacteria Optimization Algorithm(MBOA), magnetotactic bacterium multi-objective optimization algorithm (MBMOA) is proposed for solving multi-objective optimization problems(MOPs). Magnetotactic bacterium optimization algorithm is a novel random research algorithm which simulates the process of magnetotactic bacteria (MTB) producing magnetosomes(MTS) to regul...

This paper describes the first application of the Bees Algorithm to multi-objective optimisation problems. The Bees Algorithm is a search procedure inspired by the way honey bees forage for food. A standard mechanical design problem, the design of a welded beam structure, was used to benchmark the Bees Algorithm. The results obtained show the robust performance of the Bees Algorithm.