5.5 Summary
This chapter considers various combinatorial reliability optimization problems with multiple resource constraints or multiple-choice constraints incorporated for a variety of different system structures, including series systems, mixed series-parallel systems, and general systems.
Each of the problems is known as an NP-hard problem. This provided us with the motivation to develop various solution approaches, including optimal solution approaches, continuous relaxation approaches, and heuristic approaches, based on various problem-dependent solution properties. In particular, owing to the combinatorial nature of the problems, this chapter focuses on some combinatorial solution approaches, including the branch-and-bound method, the partial enumeration method, the dynamic programming method, and the greedy-type heuristic method, which can give integer optimal or heuristic solutions.
These days, metaheuristic approaches, including the simulated annealing method, the tabu search method, the neural network approach, and genetic algorithms, have been getting popular for combinatorial optimization. However, not many applications of those approaches have been made to the combinatorial reliability optimization problems yet. Thus, those approaches are not discussed here.
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Sung, C.S., Cho, Y.K., Song, S.H. (2003). Combinatorial Reliability Optimization. In: Pham, H. (eds) Handbook of Reliability Engineering. Springer, London. https://doi.org/10.1007/1-85233-841-5_5
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DOI: https://doi.org/10.1007/1-85233-841-5_5
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