Extension of a hybrid genetic algorithm for nonlinear programming problems with equality and inequality constraints

Authors:
Richard Y. K. Fung;Jiafu Tang;Dingwei Wang
Affiliations:
Department of Manufacturing Engineering & Engineering Management, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, People's Republic of China;Department of Systems Engineering, Northeastern University (NEU), Shenyang, Liaoning 110006, People's Republic of China;Department of Systems Engineering, Northeastern University (NEU), Shenyang, Liaoning 110006, People's Republic of China
Venue:
Computers and Operations Research
Year:
2002

Citing 5
Cited 8

Nonlinear programming: theory, algorithms, and applications

Nonlinear programming: theory, algorithms, and applications
Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Constrained GA Optimization

Proceedings of the 5th International Conference on Genetic Algorithms
Improving the Performance of Weighted Lagrange-Multiplier Methods for Nonlinear Constrained Optimization

ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Evolutionary algorithms for constrained parameter optimization problems

Evolutionary Computation

A line up evolutionary algorithm for solving nonlinear constrained optimization problems

Computers and Operations Research
Design optimization of wastewater collection networks by PSO

Computers & Mathematics with Applications
Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems

Expert Systems with Applications: An International Journal
An application of swarm optimization to nonlinear programming

Computers & Mathematics with Applications
A heuristic approach for allocation of data to RFID tags: A data allocation knapsack problem (DAKP)

Computers and Operations Research
Inequality constraint handling in genetic algorithms using a boundary simulation method

Computers and Operations Research
Modified harmony search optimization for constrained design problems

Expert Systems with Applications: An International Journal
Credibilitic mean-variance model for multi-period portfolio selection problem with risk control

OR Spectrum

Quantified Score

Hi-index	0.02

Visualization

Abstract

As an extension of the hybrid Genetic Algorithm-HGA proposed by Tang et al. (Comput. Math. Appl. 36 (1998) 11), this paper focuses on the critical techniques in the application of the GA to nonlinear programming (NLP) problems with equality and inequality constraints. Taking into account the equality constraints and embedding the information of infeasible points/chromosomes into the evaluation function, an extended fuzzy-based methodology and three new evaluation functions are proposed to formulate and evaluate the infeasible chromosomes. The extended version of concepts of dominated semi-feasible direction (DSFD), feasibility degree (FD1) of semi-feasible direction, feasibility degree (FD2) of infeasible points 'belonging to' feasible domain are introduced. Combining the new evaluation functions and weighted gradient direction search into the Genetic Algorithm, an extended hybrid Genetic Algorithm (EHGA) is developed to solve nonlinear programming (NLP) problems with equality and inequality constraints. Simulation shows that this new algorithm is efficient.