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A New Paradigm for the More Flexible Assembly Line Balance Study


Affiliations
1 Department of Technology Convergence, Sangmyung University, Chungnam, Korea, Republic of
2 Department of Management Engineering, Sangmyung University, Chungnam, Korea, Republic of
 

This paper proposes a new paradigm for solving Assembly Line Balancing Problems (ALBP). The task times were dealt with diverse values to investigate better design and improvement ideas.First, the problems were expressed in mixed integer models by expanding mathematical models for the simple ALBP. The proposed model could seek optimal solutions of the test problems. Furthermore, a genetic-based heuristic algorithm was proposed to handle realistic-sized problems. The test results for the candidate tasks whose task times could be reduced confirmed that the proposed algorithm utilized the candidate element tasks to seek the solutions for shortening the cycle time

Keywords

Assembly Line Balance, Genetic Algorithm, Mixed-Integer Linear Programming
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  • A New Paradigm for the More Flexible Assembly Line Balance Study

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Authors

Moon Byoung-Hoon
Department of Technology Convergence, Sangmyung University, Chungnam, Korea, Republic of
Choi Seong-Hoon
Department of Management Engineering, Sangmyung University, Chungnam, Korea, Republic of

Abstract


This paper proposes a new paradigm for solving Assembly Line Balancing Problems (ALBP). The task times were dealt with diverse values to investigate better design and improvement ideas.First, the problems were expressed in mixed integer models by expanding mathematical models for the simple ALBP. The proposed model could seek optimal solutions of the test problems. Furthermore, a genetic-based heuristic algorithm was proposed to handle realistic-sized problems. The test results for the candidate tasks whose task times could be reduced confirmed that the proposed algorithm utilized the candidate element tasks to seek the solutions for shortening the cycle time

Keywords


Assembly Line Balance, Genetic Algorithm, Mixed-Integer Linear Programming



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i18%2F114862