Abstract
Experimental tests are probably the most direct way of evaluating the performance of computer algorithms and of appealing to their users. However, there seems to be no apparent agreement regarding how to generate sample problems for the test. Commonly used random generation, for example, has several problems since that solely produces those instances which follow truly even distribution and then which do not look like “real” samples we actually encounter in the world of actuality. In this paper, we discuss what kind of properties are significant for proper generation of sample problems from a practical-mathematical point of view. Our attention is focussed mainly on the network optimization problems.
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© 1992 Springer-Verlag Berlin Heidelberg
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Iri, M. (1992). How to generate realistic sample problems for network optimization. In: Ibaraki, T., Inagaki, Y., Iwama, K., Nishizeki, T., Yamashita, M. (eds) Algorithms and Computation. ISAAC 1992. Lecture Notes in Computer Science, vol 650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56279-6_87
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DOI: https://doi.org/10.1007/3-540-56279-6_87
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