Domain Knowledge for Genetic Algorithms

نویسندگان

  • Sushil J. Louis
  • Fang Zhao
چکیده

This paper describes the encoding of domain knowledge for use by a genetic algorithm. We use the domain of system connguration design problems; speciically, the structural design and optimization of trusses to ground our discussion and results. The approach applies evolutionary principles to the optimally directed connguration design of complex structures and incorporates engineering domain knowledge into a genetic algorithm to synthesize the topology, geometry, and component properties of the structure. Preliminary results indicate that genetic algorithms with domain knowledge can generate feasible and useful designs.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A knowledge-based NSGA-II approach for scheduling in virtual manufacturing cells

This paper considers the job scheduling problem in virtual manufacturing cells (VMCs) with the goal of minimizing two objectives namely, makespan and total travelling distance. To solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (NSGA-II) and knowledge-based non-dominated sorting genetic algorithm (KBNSGA-II). The difference between these algor...

متن کامل

Pareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...

متن کامل

Design Knowledge Acquisition and Re-Use Using Genetic Engineering-Based Genetic Algorithms

This chapter describes an application of genetic engineering-based genetic algorithms as a tool for knowledge acquisition and re-use. This version of genetic algorithms is based on a model of neo-Darwinian evolution enhanced by an analysis of genetic changes, which occur during evolution, and by application of various operations that genetically engineer new organisms using the results of this ...

متن کامل

Incorporating Problem Specific Information in Genetic Algorithms

This paper describes an approach to incorporating domain knowledge into genetic algorithm search. We use genetic algorithms to attack system connguration design problems; speciically, the structural design and optimization of trusses. Since there exists a large amount of domain knowledge on this problem, we describe the incorporation of this knowledge for guiding genetic search. We outline the ...

متن کامل

Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm

This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

متن کامل

OPTIMUM PLACEMENT AND PROPERTIES OF TUNED MASS DAMPERS USING HYBRID GENETIC ALGORITHMS

Tuned mass dampers (TMDs) systems are one of the vibration controlled devices used to reduce the response of buildings subject to lateral loadings such as wind and earthquake loadings. Although TMDs system has received much attention from researchers due to their simplicity, the optimization of properties and placement of TMDs is a challenging task. Most research studies consider optimization o...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007