
doi: 10.1051/ro/2017071
Compromise solutions, as feasible points as close as possible to the ideal (utopia) point, are important solutions in multiple objective programming. It is known in the literature that each compromise solution is a properly efficient solution if the sum of the image set and conical ordering cone is closed. In this paper, we prove the same result in a general setting without any assumption.
multiple objective programming, compromise solution, properly efficient solution, Multi-objective and goal programming
multiple objective programming, compromise solution, properly efficient solution, Multi-objective and goal programming
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