An iterative genetic algorithm for the assembly line worker assignment and balancing problem of type-II

Authors:
ÖZcan Mutlu;Olcay Polat;Aliye Ayca Supciller
Affiliations:
Department of Industrial Engineering, Pamukkale University, 20070 Denizli, Turkey;Department of Industrial Engineering, Pamukkale University, 20070 Denizli, Turkey;Department of Industrial Engineering, Pamukkale University, 20070 Denizli, Turkey
Venue:
Computers and Operations Research
Year:
2013

Citing 9
Cited 3

Genetic algorithms for assembly line balancing with various objectives

Computers and Industrial Engineering - Special issue: IE in Korea
A heuristic-based genetic algorithm for workload smoothing in assembly lines

Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Benefits of Skill Chaining in Serial Production Lines with Cross-Trained Workers

Management Science
Branch and bound procedures for solving the Assembly Line Worker Assignment and Balancing Problem: Application to Sheltered Work centres for Disabled

Discrete Applied Mathematics
An efficient approach for type II robotic assembly line balancing problems

Computers and Industrial Engineering
Hybrid Metaheuristic for the Assembly Line Worker Assignment and Balancing Problem

HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
On solving the assembly line worker assignment and balancing problem via beam search

Computers and Operations Research
Simple heuristics for the assembly line worker assignment and balancing problem

Journal of Heuristics

A meta-heuristic algorithm for the fuzzy assembly line balancing type-E problem

Computers and Operations Research
A branch-and-bound algorithm for assembly line worker assignment and balancing problems

Computers and Operations Research
A heuristic and a branch-and-bound algorithm for the Assembly Line Worker Assignment and Balancing Problem

Computers and Operations Research

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this study, we consider the assembly line worker assignment and balancing problem of type-II (ALWABP-2). ALWABP-2 arises when task times differ depending on operator skills and concerns with the assignment of tasks and operators to stations in order to minimize the cycle time. We developed an iterative genetic algorithm (IGA) to solve this problem. In the IGA, three search approaches are adopted in order to obtain search diversity and efficiency: modified bisection search, genetic algorithm and iterated local search. When designing the IGA, all the parameters such as construction heuristics, genetic operators and local search operators are adapted specifically to the ALWABP-2. The performance of the proposed IGA is compared with heuristic and metaheuristic approaches on benchmark problem instances. Experimental results show that the proposed IGA is very effective and robust for a large set of benchmark problems.