Environmental Science and Engineering Group, Indian Institute of Technology, 400 076, Powai, Bombay, India.
Environ Monit Assess. 1985 Mar;5(1):21-38. doi: 10.1007/BF00396392.
Minimum Spanning Tree (MST) algorithm developed by Modak and Lohani (1984a) has been extended to consider multiple objectives for the optimum siting of ambient air monitors. Two approaches have been proposed, namely one based on the utility function and another based on the principles of sequential interactive compromise. The sequential interactive approach is heuristic but perhaps best suited to consider several objectives at a time, and particularly when professional judgements are also involved. The utility function approach may be normally restricted to two objectives at a time, but could be extended to consider a number of pollutants in the optimum design. For the purpose of illustration, the case of Taipei City, Taiwan has been considered.
由 Modak 和 Lohani（1984a）开发的最小生成树（MST）算法已经扩展到考虑多个目标，以优化环境空气监测器的选址。提出了两种方法，一种基于效用函数，另一种基于序贯交互妥协的原则。序贯交互方法是启发式的，但也许最适合一次考虑多个目标，特别是当涉及到专业判断时。效用函数方法通常可能一次只能限制考虑两个目标，但可以扩展到最优设计中考虑多个污染物。为了说明问题，考虑了台湾台北市的情况。
