Complexity Factors and Intuition‐based Methods for Facility Network Design
通过实验评估决策者使用基于情景评估的决策支持系统解决不同复杂度的设施网络设计问题，发现问题规模增大导致性能下降和方案质量波动，而增量成本改进提示能显著提升方案质量。
ABSTRACT Logistics managers frequently utilize decision support systems (DSS) to make facility network design decisions. Many DSS do not provide optimization capabilities, but instead rely on scenario evaluation as a means for developing solutions. We experimentally assessed the performances of decision makers, including experienced managers, who used four variants of a scenario evaluation‐based DSS to solve realistically sized network design problems of varying complexities. Complexity factors included DSS attributes, problem size, network types, and demand dispersion patterns. Decision makers' performances were assessed relative to optimal solutions. Overall, the decision makers generated relatively high‐quality solutions using the DSS variants. The type of design problem solved did not significantly impact problem‐solving performance. However, performance degraded and variability in solution quality escalated as problem size was increased. The availability of incremental solution cost improvement cues in the DSS significantly improved solution quality and reduced performance variability. Iconic graphic enhancements to the DSS did not consistently affect performance. However, significant interactions existed among the effects of DSS graphics capabilities, DSS information cues, and problem attributes.