Intelligent and Adaptive Multi-Objective Optimization in WANET Using Bio Inspired Algorithms

Bio-Inspired Algorithms and Preferences for Multi-objective Problems

Emergent nature inspired algorithms for multi-objective optimization

Brief description of the topic: Many real-world decision-making situations possess both a discrete or combinatorial structure and involve the simultaneous consideration of conflicting objectives. Problems of this kind are in general of large size and contains several objectives to be “optimized”. Although Multiple Objective Optimization is a well-established field of research, one branch, namel...

Bio-inspired Optimization Algorithms for Clustering

One of the ways to improve the efficiency of Information Retrieval (IR) systems is through document clustering. The search result of an IR system can be grouped or clustered so that the retrieval is made faster. Efficiency of IR systems has to be improved without compromising the quality of clusters. This paper presents a comparative study of the quality of cluster results by solving the proble...

Multi-objective Optimization using Evolutionary Algorithms

This is a progress report describing my research during the last one and a half year, performed during part A of my Ph.D. study. The research field is multi-objective optimization using evolutionary algorithms, and the reseach has taken place in a collaboration with Aarhus Univerity, Grundfos and the Alexandra Institute. My research so far has been focused on two main areas, i) multi-objective ...

Intelligent Zoning Design Using Multi-Objective Evolutionary Algorithms

This paper discusses the use of multi objective evolutionary algorithms applied to the engineering of zoning for handwriten recognition. Usually a task fulfilled by an human expert, zoning design relies on specific domain knowledge and a trial and error process to select an adequate design. Our proposed approach to automatically define the zone design was tested and was able to define zoning st...