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A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem
- Publication Year :
- 2015
- Publisher :
- Taylor & Francis Ltd, 2015.
-
Abstract
- Küçükkoç, İbrahim (Balikesir Author)<br />Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature.<br />Balikesir University Turkish Council of Higher Education
- Subjects :
- Mathematical optimization
Genetic Algorithm
Computer science
Assembly Line Balancing
Strategy and Management
Meta-Heuristics
Management Science and Operations Research
Industrial and Manufacturing Engineering
Tabu search
Computer Science Applications
Parallel Two-Sided Assembly Lines
Production planning
Artificial Intelligence
Genetic algorithm
Production Planning
Assembly line
Algorithm
Metaheuristic
Production system
Statistical hypothesis testing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....22d5b749f386c6752d676fcf97c1571c