This research presents an approach based upon ant-colony optimization to address the system reliability problem. For each component of a system, the number of units in parallel needs to be chosen to maximize the reliability for the entire system. As more parallel units are selected, costs increase in a proportional fashion. For this effort, quantity discounts for additional parallel units are considered, and the budget for purchase of parallel units is limited. Ant colony optimization methodology is employed to find an optimal system reliability that satisfies the budget constraint. The methodology is employed for several test problems, and near-optimal solutions are found.
Dorigo, M., Di Caro, G. and Gambardella, L. M. (1999) Ant Algorithms for Discrete Optimization. Artificial Life, 5, 137-172. https://doi.org/10.1162/106454699568728
Dorigo, M., Maniezzo, V. and Colorni, A. (1996) The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics—Part B, 26, 29-41. https://doi.org/10.1109/3477.484436
McMullen, P.R. and Tarasewich, P (2003) Using Ant Techniques to Solve the Assembly Line Balancing Problem. IIE Transactions, 35, 605-617.
https://doi.org/10.1080/07408170304354
Liang, Y. and Smith, A. (2007) The Ant Colony Paradigm for Reliable Systems Design. Computational Intelligence in Reliability Engineering, 40, 1-20.
https://doi.org/10.1007/978-3-540-37372-8_1
Thanitakul, P., Sa-ngiamvibool, W., Aurasopon, A. and Pothiya, S. (2013) Improved Ant Colony Optimization for Solving Reliability Redundancy Allocation Problems. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 7, 314-319.
Luo, S., Cheng, L., Ren, B. and Zhu, Q. (2014) An Improved Intelligent Ant Colony Algorithm for the Reliability Optimization Problem in Cyber-Physical Systems. Journal of Software, 9, 20-25.
