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The effectiveness of reason-based approaches for distribution network design

机译：基于原因的方法在配电网设计中的有效性

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摘要

Many operations management (OM) decisions are made in practice with only limited use of operations research tools. Instead, non-optimizing methods which rely on human reasoning and problem structuring abilities are often employed. This research assesses the effectiveness of such a method for distribution network design decisions.;Distribution network design is of key importance to a firm's strategic posture and potential for success. While there have been considerable advances in hardware and optimization software technology for network design decisions, existing optimization algorithms are not widely used and have not kept pace with the complexity of problems facing managers. Consequently, intuition, scenario evaluation, and heuristics are widely used.;The research reported here had three objectives: (1) to assess the relative effectiveness of humans using reason based approaches for facility location decisions of varying complexity, (2) to identify relationships between problem characteristics, decision maker attributes and problem solving performance, and (3) to identify effective search strategies for the scenario evaluation process. An experimental analysis of industrial managers' problem solving performances designed to achieve these objectives is described. Experimental factors included problem structure, problem size, and problem solving method. Associations between performance and subjects' demographic and cognitive attributes were also explored. Analytic techniques included ANOVA, factor analysis and multiple regression.;Performance measures were assessed relative to optimal solutions. The results indicate that the type of network problem solved has little effect on problem solving performance. Instead, the absolute number of decision variables contained in the problem is a better predictor of performance. The strength of this effect diminishes with problem size.;The pattern of solution search does not significantly affect ultimate solution quality. Decision maker experiences and usage of data are significantly associated with performance. However, all of these effects are mitigated by the availability of incremental change cost information, which provides guidance in the search process. The availability of this information dominates all other problem or user related effects.;These findings suggest that decision makers are capable of generating high quality solutions quickly using reason based approaches. However, the availability of even a small amount of guidance decreases the variability in problem solving performance significantly. Consequently, researchers should focus on extending the computational efficiency of existing algorithms and developing user friendly heuristics and optimizing techniques.
机译：在实践中，只有有限地使用运筹学工具才能做出许多运维管理（OM）决策。取而代之的是，通常采用依赖于人类推理和问题构造能力的非优化方法。这项研究评估了这种方法对配电网络设计决策的有效性。配电网络设计对于企业的战略地位和成功潜力至关重要。尽管用于网络设计决策的硬件和优化软件技术已经取得了长足的进步，但是现有的优化算法并未得到广泛使用，也无法与管理人员面临的问题的复杂性保持同步。因此，直觉，情景评估和启发式方法得到了广泛应用。；这里报道的研究具有三个目标：（1）使用基于原因的方法评估复杂程度不同的设施位置决策来评估人类的相对有效性；（2）识别关系问题特征，决策者属性和问题解决绩效之间的关系；以及（3）为情景评估过程确定有效的搜索策略。描述了旨在实现这些目标的行业经理解决问题绩效的实验分析。实验因素包括问题结构，问题大小和问题解决方法。还探讨了表现与受试者的人口统计和认知属性之间的关联。分析技术包括方差分析，因子分析和多元回归。相对于最佳解决方案，评估了性能指标。结果表明，所解决的网络问题类型对问题解决性能的影响很小。相反，问题中包含的决策变量的绝对数量可以更好地预测性能。这种影响的强度随着问题的大小而减小。;解决方案搜索的模式不会显着影响最终解决方案的质量。决策者的经验和数据使用与绩效显着相关。但是，所有这些影响都可以通过增量更改成本信息的可用性来缓解，这些信息为搜索过程提供了指导。这些信息的可用性主导着所有其他问题或与用户相关的影响。这些发现表明，决策者能够使用基于原因的方法快速生成高质量的解决方案。但是，即使是少量指导的可用性，也显着降低了解决问题性能的可变性。因此，研究人员应集中精力扩展现有算法的计算效率，并开发用户友好的启发式方法和优化技术。

著录项

  • 作者

    Swink, Morgan Lee.;

  • 作者单位

    Indiana University.;

  • 授予单位 Indiana University.;
  • 学科 Management.
  • 学位 Ph.D.
  • 年度 1992
  • 页码 182 p.
  • 总页数 182
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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