Reliability optimization using multiobjective ant colony system approaches

The multiobjective Ant Colony System (ACS) meta-heuristic has been developed successfully to provide a solution for the reliability optimization problems of series-parallel system and has been demonstrated its application to the reliability design of gear box. The problems involve the selection of components with multiple choice and redundancy levels that produce maximum benefits, and are subject to the cost and weight constraints at the system level. These are very common and realistic problems involving conceptual design of engineering system and reliability engineering. It is becoming increasingly important to develop efficient solutions to these problems because many mechanical and electrical systems are becoming more complex, even as development schedules get shorter and reliability requirements become very stringent. The multiobjective Ant Colony System algorithm offers distinct advantages to these problems compared to alternative optimization methods, and can be applied to a more diverse problem domain with respect to the type or size of the problems. Through the combination of probabilistic search, multi-objective formulation of local moves and the dynamic penalty method, the multiobjective ACSRAP, which performs very well on the redundancy apportionment problems (RAP) of the series-parallel k-out-of-n: G subsystem and reliability design of gear box, allows us to obtain an optimal design solution very frequently and more quickly than with other heuristic approaches. q 2005 Elsevier Ltd. All rights reserved.