Lai C.-A.Chang C.-T.Ko C.-L.Chen C.-L.2019-05-212019-05-21200308885885https://scholars.lib.ntu.edu.tw/handle/123456789/409693A mathematical programming model has been developed in this study to determine the best measurement locations in a given process network and also the optimal numbers of redundant and spare sensors used in a corrective maintenance program. The model solution yields the maximum system availability under a set of user supplied limitations on life-cycle cost and/or estimator's precision. Genetic algorithms were used to identify the optimum in an evolutionary process. The usefulness of the proposed approach is demonstrated with extensive case studies.journal article10.1021/ie020567j2-s2.0-0141656472https://www.scopus.com/inward/record.uri?eid=2-s2.0-0141656472&doi=10.1021%2fie020567j&partnerID=40&md5=3be8c31b50686cf5caa3ec71aea5ba66