Elitism in agent-based evolutionary multiobjective optimization
نویسندگان
چکیده
This work introduces a new evolutionary approach to solving the problems of multiobjective optimization. Novelty of the proposed method consists in the application of an evolutionary multi-agent system equipped with the mechanism(s) of elitism, instead of its ’classical’ (non-elitist) version. In the paper the model of an elitist evolutionary multi-agent system is described together with its sample realization, and preliminary experimental results.
منابع مشابه
The Role of Elitism in Multiobjective Optimization with Evolutionary Algorithms
This paper studies the influence of elitism in Evolutionary Multiobjective Optimization. The true efficiency of inserting elitism in these algorithms was not yet sufficiently developed. Many algorithms for multiobjective optimization use different methods to keep the best individuals (the elite) founded on the duration of the search process. The problem is how this elitism can be preserved and,...
متن کاملCurrent and Future Research Trends in Evolutionary Multiobjective Optimization
In this chapter we present a brief analysis of the current research performed on evolutionary multiobjective optimization. After analyzing first and second generation multiobjective evolutionary algorithms, we address two important issues: the role of elitism in evolutionary multiobjective optimization and the way in which concepts from multiobjective optimization can be applied to constraint-h...
متن کاملEvolutionary multiobjective optimization using a cultural algorithm
In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from the specialized literature. Our results are compared with respect to the NSGA-II, which is an algorithm r...
متن کاملPareto-based continuous evolutionary algorithms for multiobjective optimization
In an attempt to solve multiobjective optimization problems, many traditional methods scalarize an objective vector into a single objective by a weight vector. In these cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands a user to have knowledge about the underlying problem. Moreover, in solving multiobjective problems, designers m...
متن کاملEvolutionary Algorithms for Multiobjective Optimization
Multiple, often conflicting objectives arise naturally in most real-world optimization scenarios. As evolutionary algorithms possess several characteristics due to which they are well suited to this type of problem, evolution-based methods have been used for multiobjective optimization for more than a decade. Meanwhile evolutionary multiobjective optimization has become established as a separat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial
دوره 9 شماره
صفحات -
تاریخ انتشار 2005