Abstract
One of the keys to the successful application of vector-maximum methods involves reducing the gradient cone using interval criterion weights. In this paper, the gradient cone is defined to be the convex cone generated by the gradients of the different objectives. Methods are given for reducing the gradient cone to subsets of itself under different circumstances. These circumstances include fixed and/ or interval criterion weights and the effect of linear dependence among the original criterion gradients on results. Illustrative examples are provided and computational implications are discussed.
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References
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© 1978 Springer-Verlag Berlin Heidelberg
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Steuer, R.E. (1978). Vector-Maximum Gradient Cone Contraction Techniques. In: Zionts, S. (eds) Multiple Criteria Problem Solving. Lecture Notes in Economics and Mathematical Systems, vol 155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46368-6_23
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DOI: https://doi.org/10.1007/978-3-642-46368-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-08661-1
Online ISBN: 978-3-642-46368-6
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