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. Keywords: Disjoint Minimal Paths, Multi-Objective Components Assignment Problem, Stochastic-Flow Network, System Reliability, Total Lead-time
Highlights
The reliability of a Stochastic Flow Network (SFN) under a time constraint is defined as the probability that the SFN can send the required amount of data from the source to the sink within a specified amount of time1
In5, the quickest path problem was modified to evaluate the system reliability such that data could be sent from the source to the sink through two disjoint Minimal Paths (MPs) given a time constraint
The results obtained in table 2 are compared with that obtained by9 for the same problem. we found that the results is closed to [9] for d=6 and T=7 at the weights (0.9, 0.1)
Summary
The reliability of a Stochastic Flow Network (SFN) under a time constraint is defined as the probability that the SFN can send the required amount of data from the source to the sink within a specified amount of time. The reliability of a Stochastic Flow Network (SFN) under a time constraint is defined as the probability that the SFN can send the required amount of data from the source to the sink within a specified amount of time1 In this case, each link has two attributes: the lead-time and the capacity. In5, the quickest path problem was modified to evaluate the system reliability such that data could be sent from the source to the sink through two disjoint Minimal Paths (MPs) given a time constraint.
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