GREY INTEGER PROGRAMMING - AN APPLICATION TO WASTE MANAGEMENT PLANNING UNDER UNCERTAINTY
GREY INTEGER PROGRAMMING - AN APPLICATION TO WASTE MANAGEMENT PLANNING UNDER UNCERTAINTY
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DOI：
10.1016/0377-2217(94)00093-r
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发表时间：
1995-06-22
影响因子：
6.4
通讯作者：
PATRY, GG
中科院分区：
文献类型：
--
作者：
HUANG, GH;BAETZ, BW;PATRY, GG
将灰色数和灰色数学规划的概念引入到混合整数线性规划优化框架中，提出了不确定条件下设施扩建规划的灰色整数规划方法。该方法在技术特点和适用性方面都是对以往整数规划方法的改进。它允许将不确定信息有效地传达到优化过程和最终解决方案中。该方法计算量小，适用于实际问题。模拟方法应用于一个区域固体废物管理系统内的废物流量分配和处理/处置设施扩展的假设规划问题。二元变量解提供了多时期、多设施、多尺度环境下不同发展方案的范围，连续变量解提供了目标函数值的上界和下界所对应的废物流分配的最优方案。结果表明，该方法可以得到合理、实用的解决方案。
This paper introduces a grey integer programming (GIP) method for facility expansion planning under uncertainty, by incorporating the concepts of grey number and grey mathematical programming into a mixed integer linear programming optimization framework. The approach is an improvement upon previous integer programming methods in terms of its technical characteristics and applicability. It allows uncertain information to be effectively communicated into the optimization process and the resulting solutions. It also has low computational requirements and is thus applicable to practical problems. The modelling approach is applied to a hypothetical planning problem of waste flow allocation and treatment/disposal facility expansion within a regional solid waste management system. The binary variable solutions provide the ranges of different development alternatives within a multi-period, multi-facility and multi-scale context, and the continuous variable solutions provide optimal schemes for waste flow allocation corresponding to the upper and lower bounds of the objective function value. The results indicate that reasonable and useful solutions can be achieved through the developed approach.