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Shortest-Path Optimization of Ship Diesel Engine Disassembly and Assembly Based on AND/OR Network

机译:基于和/或网络的船舶柴油发动机拆卸和组装的最短路径优化

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Ship diesel engine disassembly and assembly (SDEDA) is essential for ship inspection and maintenance and navigation safety. 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&A). Considering the “AND” and “OR” relations (modeled as links) among the D&A operations (modeled as nodes), an “AND/OR” network is developed to extend a specialized graph model for the D&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&A operations. To the best of our knowledge, it is the first try to formulate the D&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&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.
机译:船舶柴油发动机拆卸和装配(Sdeda)对于船舶检查和维护和导航安全至关重要。 Sdeda包括各种机械零件和操作。开发一种Sydeda操作系统来提高拆卸和组装(D&A)的效率至关重要。考虑D&A操作中的“和”和“或”或“关系(建模为链接)(以节点建模),”和/或“网络是开发的,以扩展教育背景下的D&A测序问题的专业图形模型和培训。然后,我们设计了混合整数线性程序(MILP),以基于和/或网络优化Sydeda序列。考虑到和/或网络中的流量平衡,我们使用广度第一,分支切割和深度第一策略开发了精确的算法和随机搜索算法,以最大限度地减少代表D&A操作序列最佳序列的最短路径的成本。据我们所知,它是第一次尝试通过扩展网络模型制定D&A操作。数值实验表明,所提出的算法实用,用于解决具有2000多个D&A操作的大规模实例。广度第一最短路径算法从解决方案质量和计算时间的角度胜过MILP求解器,并且所有开发的算法都是在计算时间方面具有竞争力的。

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