![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
Multi-Objective Components Assignment Problem Subject to Lead-Time Constraint
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.
User
Information
- Lin Y. Extend the quickest path problem to the system reliability evaluation for a stochastic-flow network. Computers and Operation Research. 2003; 30:567–75. Crossref
- Chen YL, Chin YH. The quickest path problem. Computers and Operations Research. 1990; 17(2):153–61. Crossref
- Chen GH, Hung YC. On the quickest path problem. Information Processing Letters. 1993; 46:125–8. Crossref
- Martins VQE, Santos JLE. An algorithm for the quickest path problem. Operations Research Letters. 1997 May; 20(4):195–8. Crossref
- Lin YK. Time version of the shortest path problem in a stochastic-flow network. Journal of Computational and Applied Mathematics. 2009; 228:150–7. Crossref
- Lin YK. On performance evaluation for a multistate network under spare routing. Information Sciences. 2012; 203:73–82. Crossref
- Lin YK, Yeh CT. Evaluation of optimal network reliability under Components-Assignments subject to a transmission budget. Transactions on Reliability. 2010 Sep; 59(3):539–50.
- Lin YK, Yeh CT. Maximizing network reliability for stochastic transportation networks under a budget constraint by using a genetic algorithm. International Journal of Innovative Computing Information and Control ICIC. 2011; 7(12):7033–50.
- Hassan MR. Solving a component assignment problem for a stochastic flow network under lead-time constraint. Indian Journal of Science and Technology 2015; 8(35):1-5.
- Coello CA, Christiansen AD. Multi objective optimization of trusses using genetic algorithms. Computers and Structures. 2000; 75:647–60. Crossref
- Konak A, Coit DW, Smith AE. Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering and System Safety. 2006; 91:992–1007. Crossref
- Lin YK, Yeh CT. A two-stage approach for a multi-objective component assignment problem for a stochastic-flow network. Engineering Optimization. 2013; 45(3):265–85. Crossref
- Deb K, Pratap K, Agarwal S, Meyarivan T. A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation. 2002 Apr; 6(2):182–98. Crossref
- Brownlee AEI, Wright JA. Constrained, mixed-integer and multi-objective optimization of building designs by NSGA-II with fitness approximation. Applied Soft Computing Journal. 2015; 35:114–26. Crossref
- Chatterjee S, Abhishek K, Mahapatra SS, Datta S, Yadav RK. NSGA-II approach of optimization to study the effects of drilling parameters in AISI-304 stainless steel. Procedia Engineering. 2014; 97:78–84. Crossref
- Pasandideh SHR, Niaki STA, Asadi K. Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Sciences. 2015 Jan; 292:57–74. Crossref
- Xue J. On multistate system analysis. IEEE Transactions on Reliability. 1985; 34(4):329–37.
- Chen SG, Lin YK. Search for all minimal paths in a general large flow network. IEEE Transactions on Reliability. 2012; 61(4):949–56. Crossref.
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 222
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 0