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Some problems in sequencing and scheduling utilizing branch and bound algorithms.

机译:利用分支定界算法进行排序和调度的一些问题。

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This dissertation deals with branch and bound algorithms which are applied to the two-machine flow-shop problem with sparse precedence constraints and the optimal sequencing and scheduling of multiple feedstocks in a batch type digester problem. The common characteristic of these problems is that they are combinatorial optimization problems of the sequencing and scheduling class. Branch and bound methods are the natural approaches for these problems classes. The objective of this research is to derive efficient branch and bound algorithms for these problems.;An efficient solution of the problem with parallel-chain precedence constraints was developed by Kurisu in 1976. The problem studied here is to find a schedule which minimizes the maximum flow time with the requirement that the schedule does not violate a set of sparse precedence constraints. This research provides a branch and bound algorithm which employs a lower bounding rule and is based on an adjustment of the sequence obtained by applying Johnson's algorithm. It is demonstrated that this lower bounding procedure in conjunction with Kurisu's branching rule is effective for the sparse precedence constraints problem class.;Biomass to methane production systems have the potential of supplying 25% of the national gas demand. The production systems associated with this conversion process are anaerobic digestion facilities. The economic viability of these systems depends a great deal on cost effective production methods and facilities. The optimal operation of a batch digester system requires the sequencing and scheduling of all batches from multiple feedstocks during a fixed time horizon. A significant characteristic of these systems is that the feedstock decays in storage before use in the digester system. The operational problem is to determine the time to allocate to each batch of several feedstocks and then sequence the individual batches so as to maximize biogas production for a single batch type digester over a fixed planning horizon. This research provides a branch and bound algorithm for sequencing and a two-step hierarchical dynamic programming procedure for time allocation scheduling. An efficient heuristic algorithm is developed for large problems and demonstrated to yield excellent results.
机译:本文研究了分支定界算法,该算法适用于具有稀疏优先约束的两机流水车间问题,并且适用于间歇式消化池问题中多种原料的最优排序和调度。这些问题的共同特征是它们是排序和调度类的组合优化问题。分支定界方法是这些问题类别的自然方法。这项研究的目的是为这些问题导出有效的分支定界算法。1976年Kurisu开发了具有并行链优先约束的问题的有效解决方案。这里研究的问题是找到一个最小化最大调度的时间表。流时间,要求调度不违反一组稀疏优先级约束。这项研究提供了一种分支定界算法,该算法采用较低的定界规则,并且基于对通过应用Johnson算法获得的序列的调整。证明了这种下限过程结合Kurisu的分支规则对于稀疏优先约束问题类别是有效的。甲烷生产系统的生物质有潜力满足全国天然气需求的25%。与该转化过程相关的生产系统是厌氧消化设备。这些系统的经济可行性在很大程度上取决于具有成本效益的生产方法和设施。批处理消化器系统的最佳运行需要在固定的时间范围内对来自多种原料的所有批处理进行排序和调度。这些系统的显着特征是原料在消化系统中使用前在存储中会腐烂。操作上的问题是确定分配给每批几种原料的时间,然后对各个批进行排序,以便在固定的计划范围内最大化单个批式消化器的沼气产量。该研究提供了一种用于排序的分支定界算法和一个用于时间分配调度的两步分层动态规划程序。针对大问题开发了一种有效的启发式算法,并证明可产生出色的结果。

著录项

  • 作者

    Gim, Bongjin.;

  • 作者单位

    Texas A&M University.;

  • 授予单位 Texas A&M University.;
  • 学科 Industrial engineering.
  • 学位 Ph.D.
  • 年度 1988
  • 页码 59 p.
  • 总页数 59
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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