Genetic Algorithm for Multiobjective Optimization and Life-cycle Cost

Abstract

Genetic algorithms (GA) have the characteristic of maintaining a population of solutions, and can search in a parallel manner for many nondominated solutions. These features coincide with the requirement of seeking a Pareto optimal set in a multiobjective optimization problem. A Pareto GA whose goal is to locate the Pareto optimal set of a multiobjective optimization problem is developed along with Pareto-filter in order not to miss Pareto optimal points during evolutionary processes.

Department(s)

Civil, Architectural and Environmental Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

C© 2024 American Society of Civil Engineers, All rights reserved.

Publication Date

01 Dec 1999

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