Improving the genetic algorithms performance in simple assembly line balancing

Authors:
Seren Özmehmet Tasan;Semra Tunali
Affiliations:
Department of Industrial Engineering, Dokuz Eylul University, Bornova, Izmir, Turkey;Department of Industrial Engineering, Dokuz Eylul University, Bornova, Izmir, Turkey
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part V
Year:
2006

Citing 5
Cited 1

An introduction to genetic algorithms

An introduction to genetic algorithms
Genetic algorithms for assembly line balancing with various objectives

Computers and Industrial Engineering - Special issue: IE in Korea
Tabu Search

Tabu Search
A Hybrid Genetic Algorithm for Assembly Line Balancing

Journal of Heuristics
Evaluating performance advantages of grouping genetic algorithms

Engineering Applications of Artificial Intelligence

A Review on the Application of Hybrid Artificial Intelligence Systems to Optimization Problems in Operations Management

HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a hybrid GA approach combining genetic algorithm (GA) and tabu search (TS) is proposed to solve simple assembly line balancing problem. As this problem is combinatorial and NP hard in nature, the optimum seeking methods are impractical. Therefore, we proposed a hybrid approach, which unites the advantages and mitigates the disadvantages of the two algorithms. To increase the performance of the hybrid GA, we also optimized the control parameters such as the population size, rate of crossover and mutation. Moreover, to gain more insight on the performance of hybrid GA, we implemented it to various benchmark problems and observed that the hybridization of GA with TS improves the solution performance of the balancing problem.