Application Issues for Multiobjective Evolutionary Algorithms
نویسنده
چکیده
Abstract: Various issues of the design and application of multiobjective evolutionary algorithms to real-life optimization problems are discussed. In particular, questions on problem-specific data structures and evolutionary operators and the determination of method parameters are treated. Three application examples in the areas of constrained global optimization (electronic circuit design), semi-infinite programming (design centering problems), and discrete optimization (project scheduling) are discussed.
منابع مشابه
Applying multiobjective evolutionary algorithms in industrial projects
During the recent years, multiobjective evolutionary algorithms have matured as a flexible optimization tool which can be used in various areas of real-life applications. Practical experiences showed that typically the algorithms need an essential adaptation to the specific problem for a successful application. Considering these requirements, we discuss various issues of the design and applicat...
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 Algorithms for the Multiobjective Shortest Path Problem
This paper presents an overview of the multiobjective shortest path problem (MSPP) and a review of essential and recent issues regarding the methods to its solution. The paper further explores a multiobjective evolutionary algorithm as applied to the MSPP and describes its behavior in terms of diversity of solutions, computational complexity, and optimality of solutions. Results show that the e...
متن کاملMultiobjective Evolutionary Algorithm Approach For Solving Integer Based Optimization Problems
Multiobjective Evolutionary algorithms (MOEAs) are often well-suited for complex combinatorial Multiobjective optimization problems (MOPs). Integer based MOPs are prevalent in real world applications where there exist a discrete amount of a component or quantity of an item. Presented here is the application of a building block based MOEA, the MOMGA-II, to a NP Complete problem and real-world ap...
متن کاملMultiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems
Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...
متن کامل