Multi-choice goal programming with utility functions
Multi-choice goal programming with utility functions
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DOI：
10.1016/j.ejor.2011.06.041
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发表时间：
2011-12-01
影响因子：
6.4
通讯作者：
Chang, Ching-Ter
中科院分区：
文献类型：
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作者：
Chang, Ching-Ter
目标规划（GP）是求解多准则决策问题和多目标决策问题的一种最广泛使用的方法，方法是寻找一组满意的解。然而，目标规划的主要限制是只能使用带标量值的期望水平来解决多目标问题。为了解决这一问题，Chang （2007a）提出了多选择目标规划（MCGP）。本文在继承MCGP思想的基础上，提出了效用函数中水平实现的新概念，将经典GP和MCGP中的期望水平替换为标量值。根据这一思想，利用MCGP的技能和效用函数来解决多目标问题是可能的。使用MCGP的效用函数的主要贡献是，它们可以作为衡量工具，帮助决策者制定与他们的目标相对应的最佳/适当的政策，实现最高的效用水平。此外，上述属性可以提高MCGP在解决更多现实世界的决策/管理问题方面的实际效用。(C) 2011 Elsevier B.V.版权所有
Goal programming (GP) has been, and still is, the most widely used technique for solving multiple-criteria decision problems and multiple-objective decision problems by finding a set of satisfying solutions. However, the major limitation of goal programming is that can only use aspiration levels with scalar value for solving multiple objective problems. In order to solve this problem multi-choice goal programming (MCGP) was proposed by Chang (2007a). Following the idea of MCGP this study proposes a new concept of level achieving in the utility functions to replace the aspiration level with scalar value in classical GP and MCGP for multiple objective problems. According to this idea, it is possible to use the skill of MCGP with utility functions to solve multi-objective problems. The major contribution of using the utility functions of MCGP is that they can be used as measuring instruments to help decision makers make the best/appropriate policy corresponding to their goals with the highest level of utility achieved. In addition, the above properties can improve the practical utility of MCGP in solving more real-world decision/management problems. (C) 2011 Elsevier B.V. All rights reserved.