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Syst."],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Manufacturing resources allocation (MRA) is important area, and a significant challenge is encountered when considering high value, customized, complex structure and long lifespan of complex product system (CoPS). The relationship between uncertainty factors (i.e., inputs and outputs) of processes in CoPS\u2019s manufacturing, operation and maintenance needs comprehensive trade-offs in the preliminary MRA stage. Meanwhile, the CoPS\u2019s MRA schemes are contradictory from a customer\u2019s perspective with different emphasis on operating cost related to operation and maintenance stage. These problems are unavailable in traditional expressions for model and objective function. In this paper, a new variant of MRA multi-criteria decision-making (MCDM) model of CoPS (MRA&amp;CoPS) is developed to evaluate MRA schemes with considering CoPS\u2019s lifecycle. Meanwhile, considering characteristics of CoPS and customer-involved MRA process, the three-layer criteria cumulative model is established. In the proposed method, intuitionistic fuzzy sets (IFSs) based subjective\u2013objective hybrid fuzzy method is presented to deal with uncertainty of evaluation criteria. The weights of criteria are determined by the proposed intuitionistic fuzzy information entropy (IFIE). The hybrid IFIE-TOPSIS method is proposed to obtain the optimum MRA scheme by ranking results. An example of CoPS\u2019s MRA in a case enterprise is addressed to verify the rationality and validity of the proposed method. The results show that the proposed method is more preferable and robust in MCDM problem of MRA&amp;CoPS.<\/jats:p>","DOI":"10.1007\/s40747-022-00960-x","type":"journal-article","created":{"date-parts":[[2023,2,25]],"date-time":"2023-02-25T05:02:38Z","timestamp":1677301358000},"page":"5013-5032","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-criteria decision-making of manufacturing resources allocation for complex product system based on intuitionistic fuzzy information entropy and TOPSIS"],"prefix":"10.1007","volume":"9","author":[{"given":"Xu","family":"Luo","sequence":"first","affiliation":[]},{"given":"Shunsheng","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6088-1546","authenticated-orcid":false,"given":"Baigang","family":"Du","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Tian","family":"Tan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,25]]},"reference":[{"key":"960_CR1","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.jengtecman.2014.06.002","volume":"33","author":"O Dedehayir","year":"2014","unstructured":"Dedehayir O, Nokelainen T, M\u00e4kinen SJ (2014) Disruptive innovations in complex product systems industries: a case study. 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