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The SDEDA consists of various machinery parts and operations. It is crucial to develop a system of SDEDA operations to improve the efficiency of disassembly and assembly (D&amp;A). Considering the \u201cAND\u201d and \u201cOR\u201d relations (modeled as links) among the D&amp;A operations (modeled as nodes), an \u201cAND\/OR\u201d network is developed to extend a specialized graph model for the D&amp;A sequencing problem in the context of education and training. Then, we devised a mixed-integer linear program (MILP) to optimize the SDEDA sequence based on the AND\/OR network. Considering the flow balance in the AND\/OR network, we developed exact algorithms and random search algorithms using breadth-first, branch cut and depth-first strategies to minimize the cost of the shortest path that represents an optimal sequence of D&amp;A operations. To the best of our knowledge, it is the first try to formulate the D&amp;A operations by an extended network model. Numerical experiments show that the proposed algorithms are practical for solving large-scale instances with more than 2000 D&amp;A operations. The breadth-first shortest-path algorithm outperforms the MILP solver from the perspective of solution quality and computing time, and all developed algorithms are competitive in terms of computing time.<\/jats:p>","DOI":"10.1155\/2020\/2919615","type":"journal-article","created":{"date-parts":[[2020,2,18]],"date-time":"2020-02-18T18:31:14Z","timestamp":1582050674000},"page":"1-15","source":"Crossref","is-referenced-by-count":4,"title":["Shortest-Path Optimization of Ship Diesel Engine Disassembly and Assembly Based on AND\/OR Network"],"prefix":"10.1155","volume":"2020","author":[{"given":"Deng-Zhi","family":"Chen","sequence":"first","affiliation":[{"name":"Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1804-0468","authenticated-orcid":true,"given":"Chen","family":"Wei","sequence":"additional","affiliation":[{"name":"Logistics Research Center, Shanghai 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