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Multi-Objective Components Assignment Problem Subject to Lead-Time Constraint


Affiliations
1 Computer Science Branch, Department of Mathematics, Aswan University, Aswan, Egypt
 

Objectives: The study aims to present a multi objective genetic algorithm in order to solve multi-objective components assignment problem subject to lead-time constraints. Methods/Statistical Analysis: The study has used non-dominated sorting genetic algorithm II to solve component assignment problems under total lead-time constraints and determine the most optimal solution characterized by a maximum reliability and minimum total lead-time. The proposed method is tested on different examples from the literature to illustrate its efficiency in comparison with a single genetic algorithm. Findings: The proposed algorithm succeeded in identifying the optimal solution to the presented problem in comparison with the single genetic algorithm without guessing or determining the initial value for the total lead-time. Moreover, similar observation was identified for the six-node network example. However, no comparison for TANET example was present because there is no literature dealt it for the presented problem. The proposed approach succeeded by obtaining the most optimal solution to the presented problem. Application/Improvements: With the help of proposed approach, the system reliability is maximized and total lead-time is minimized. Future researches may focus on other algorithms to improve the reliability and lead-time.
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  • Multi-Objective Components Assignment Problem Subject to Lead-Time Constraint

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Authors

M. R. Hassan
Computer Science Branch, Department of Mathematics, Aswan University, Aswan, Egypt
H. Abdou
Computer Science Branch, Department of Mathematics, Aswan University, Aswan, Egypt

Abstract


Objectives: The study aims to present a multi objective genetic algorithm in order to solve multi-objective components assignment problem subject to lead-time constraints. Methods/Statistical Analysis: The study has used non-dominated sorting genetic algorithm II to solve component assignment problems under total lead-time constraints and determine the most optimal solution characterized by a maximum reliability and minimum total lead-time. The proposed method is tested on different examples from the literature to illustrate its efficiency in comparison with a single genetic algorithm. Findings: The proposed algorithm succeeded in identifying the optimal solution to the presented problem in comparison with the single genetic algorithm without guessing or determining the initial value for the total lead-time. Moreover, similar observation was identified for the six-node network example. However, no comparison for TANET example was present because there is no literature dealt it for the presented problem. The proposed approach succeeded by obtaining the most optimal solution to the presented problem. Application/Improvements: With the help of proposed approach, the system reliability is maximized and total lead-time is minimized. Future researches may focus on other algorithms to improve the reliability and lead-time.

References





DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i21%2F100080