Genetic algorithm for multi-objective experimental optimization
نویسندگان
چکیده
منابع مشابه
Genetic algorithm for multi-objective experimental optimization
A new software tool making use of a genetic algorithm for multi-objective experimental optimization (GAME.opt) was developed based on a strength Pareto evolutionary algorithm. The software deals with high dimensional variable spaces and unknown interactions of design variables. This approach was evaluated by means of multi-objective test problems replacing the experimental results. A default pa...
متن کاملCellular Genetic Algorithm for Multi-Objective Optimization
In this paper, we show how cellular structures can be combined with a multi-objective genetic algorithm (MOGA) for improving its search ability to find Pareto-optimal solutions of multi-objective optimization problems. We propose an assignment method of a different search direction to each cell for implementing a cellular MOGA. In our cellular MOGA, every individual in each population exists in...
متن کاملMULTI-OBJECTIVE OPTIMIZATION OF TIME-COST-SAFETY USING GENETIC ALGORITHM
Safety risk management has a considerable effect on disproportionate injury rate of construction industry, project cost and both labor and public morale. On the other hand time-cost optimization (TCO) may earn a big profit for project stakeholders. This paper has addressed these issues to present a multi-objective optimization model to simultaneously optimize total time, total cost and overall ...
متن کاملMessy Genetic Algorithm Based Multi-Objective Optimization 1 Messy Genetic Algorithm Based Multi-Objective Optimization: A Comparative Statistical Analysis
Many real-world scientific and engineering applications involve finding solutions to “hard” Multiobjective Optimization Problems (MOPs). Genetic Algorithms (GAs) can be extended to find acceptable MOP Pareto solutions. The intent of this discussion is to illustrate that modifications made to the Multi-Objective messy GA (MOMGA) have further improved the efficiency of the algorithm. The MOMGA is...
متن کاملNeighborhood Cultivation Genetic Algorithm for Multi-Objective Optimization Problems
In this paper, we propose a new genetic algorithm for multi-objective optimization problems. That is called “Neighborhood Cultivation Genetic Algorithm (NCGA)”. NCGA includes the mechanisms of other methods such as SPEA2 and NSGA-II. Moreover, NCGA has the mechanism of neighborhood crossover. Because of the neighborhood crossover, the effective search can be performed and good results can be de...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioprocess and Biosystems Engineering
سال: 2006
ISSN: 1615-7591,1615-7605
DOI: 10.1007/s00449-006-0087-7