Improved Ant Colony Optimization for Solving Reliability Redundancy Allocation Problems
This paper presents an improved ant colony optimization (IACO) for solving the reliability redundancy allocation problem (RAP) in order to maximize system reliability. To improve the performance of ACO algorithm, two additional techniques, i.e. neighborhood search, and re-initialization process are presented. To show its efficiency and effectiveness, the proposed IACO is applied to solve three RAPs. Additionally, the results of the proposed IACO are compared with those of the conventional heuristic approaches i.e. genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The experimental results show that the proposed IACO approach is comparatively capable of obtaining higher quality solution and faster computational time.
[1] Kuo W, Prasad VR. "An annotated overview of system-reliability optimization.” IEEE Transactions on Reliability, vol. 49 (2), pp. 176-187, 2000.
[2] Chen TC, You PS. "Immune algorithm based approach for redundant reliability problems.” Computers in Industry, vol. 56, pp. 195-205, 2005.
[3] Coit DW, Smith AE. "Reliability optimization of series-parallel systems using a genetic algorithm.” IEEE Transactions on Reliability vol. 45, pp. 254-260, 1996.
[4] Liang YC, Chen YC. "Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm.” Reliability Engineering and System Safety vol. 92, pp.323-331, 2007.
[5] Hsieh YC. "A linear approximation for redundant reliability problems with multiple component choices.” Computers and Industrial Engineering vol. 44, pp. 91-103, 2003.
[6] Onishi J, Kimura S, James RJW, Nakagawa Y. "Solving the redundancy allocation problem with a mix of components using the improved surrogate constraint method.” IEEE Transactions on Reliability vol. 56(1), pp.94-101, 2007.
[7] Colorni A, Dorigo M, Maniezzo V. "Distributed optimization by ant colonies.” In: Proceedings of the European conference on artificial life; pp. 134-142, 1991.
[8] Dorigo M, Maniezzo V, Colorni A. "Ant system: optimization by a colony of cooperative agents.” IEEE Trans Syst Man Cybernet B: Cybernet vol. 26(1), pp.29-41, 1996.
[9] Dorigo M, Gambardella LM. "Ant colonies for the traveling salesman problem. Bio systems, vol. 43, pp. 73-81, 1997.
[10] Dorigo M, Gambardella LM. "Ant colony system: a cooperative learning approach to the traveling salesman problem.” IEEE Trans Evol Comput vol. 1(1), pp.53-66, 1997.
[11] Gambardella LM, Taillard E, Dorigo M. "Ant colonies for the quadratic assignment problem.” J Operat Res Soc vol. 50, pp. 167-176, 1999.
[12] Bell J, McMullen P. "Ant colony optimization techniques for the vehicle routing problem.” Adv Eng Inform vol. 18, pp. 41-48, 2004.
[13] Wei-Chang Yeh, Tsung-Jung Hsieh, "Solving reliability redundancy allocation problems using an artificial bee colony algorithm,” Computer & Operations Research, vol.38, pp. 1465-1473, 2011.
[14] Kanyapat W., Paramote W, "Reliability optimization of topology communication network design using an improved ant colony optimization,” Computer and electrical engineering, vol. 35, pp.730-747, 2009.
[15] Manju Agarwal, Vikas K. Sharma, "Ant colony approach to constrained redundancy optimization in binary systems,” Applied Mathematical Modeling, vol. 34, pp. 992-1003, 2010.
[16] W. Kuo, V.R. Prasad, F.A. Tillman, C.L. Hwang, "Optimal Reliability Design-fundamentals and Applications,” Cambridge Press, Cambridge, 2001.
[1] Kuo W, Prasad VR. "An annotated overview of system-reliability optimization.” IEEE Transactions on Reliability, vol. 49 (2), pp. 176-187, 2000.
[2] Chen TC, You PS. "Immune algorithm based approach for redundant reliability problems.” Computers in Industry, vol. 56, pp. 195-205, 2005.
[3] Coit DW, Smith AE. "Reliability optimization of series-parallel systems using a genetic algorithm.” IEEE Transactions on Reliability vol. 45, pp. 254-260, 1996.
[4] Liang YC, Chen YC. "Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm.” Reliability Engineering and System Safety vol. 92, pp.323-331, 2007.
[5] Hsieh YC. "A linear approximation for redundant reliability problems with multiple component choices.” Computers and Industrial Engineering vol. 44, pp. 91-103, 2003.
[6] Onishi J, Kimura S, James RJW, Nakagawa Y. "Solving the redundancy allocation problem with a mix of components using the improved surrogate constraint method.” IEEE Transactions on Reliability vol. 56(1), pp.94-101, 2007.
[7] Colorni A, Dorigo M, Maniezzo V. "Distributed optimization by ant colonies.” In: Proceedings of the European conference on artificial life; pp. 134-142, 1991.
[8] Dorigo M, Maniezzo V, Colorni A. "Ant system: optimization by a colony of cooperative agents.” IEEE Trans Syst Man Cybernet B: Cybernet vol. 26(1), pp.29-41, 1996.
[9] Dorigo M, Gambardella LM. "Ant colonies for the traveling salesman problem. Bio systems, vol. 43, pp. 73-81, 1997.
[10] Dorigo M, Gambardella LM. "Ant colony system: a cooperative learning approach to the traveling salesman problem.” IEEE Trans Evol Comput vol. 1(1), pp.53-66, 1997.
[11] Gambardella LM, Taillard E, Dorigo M. "Ant colonies for the quadratic assignment problem.” J Operat Res Soc vol. 50, pp. 167-176, 1999.
[12] Bell J, McMullen P. "Ant colony optimization techniques for the vehicle routing problem.” Adv Eng Inform vol. 18, pp. 41-48, 2004.
[13] Wei-Chang Yeh, Tsung-Jung Hsieh, "Solving reliability redundancy allocation problems using an artificial bee colony algorithm,” Computer & Operations Research, vol.38, pp. 1465-1473, 2011.
[14] Kanyapat W., Paramote W, "Reliability optimization of topology communication network design using an improved ant colony optimization,” Computer and electrical engineering, vol. 35, pp.730-747, 2009.
[15] Manju Agarwal, Vikas K. Sharma, "Ant colony approach to constrained redundancy optimization in binary systems,” Applied Mathematical Modeling, vol. 34, pp. 992-1003, 2010.
[16] W. Kuo, V.R. Prasad, F.A. Tillman, C.L. Hwang, "Optimal Reliability Design-fundamentals and Applications,” Cambridge Press, Cambridge, 2001.
@article{"International Journal of Information, Control and Computer Sciences:66017", author = "Phakhapong Thanitakul and Worawat Sa-ngiamvibool and Apinan Aurasopon and Saravuth Pothiya", title = "Improved Ant Colony Optimization for Solving Reliability Redundancy Allocation Problems", abstract = "This paper presents an improved ant colony optimization (IACO) for solving the reliability redundancy allocation problem (RAP) in order to maximize system reliability. To improve the performance of ACO algorithm, two additional techniques, i.e. neighborhood search, and re-initialization process are presented. To show its efficiency and effectiveness, the proposed IACO is applied to solve three RAPs. Additionally, the results of the proposed IACO are compared with those of the conventional heuristic approaches i.e. genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The experimental results show that the proposed IACO approach is comparatively capable of obtaining higher quality solution and faster computational time.
", keywords = "Ant colony optimization, Heuristic algorithm, Mixed-integer nonlinear programming, Redundancy allocation problem, Reliability optimization.", volume = "7", number = "2", pages = "319-6", }
