2017
DOI: 10.1007/s12190-017-1140-1
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A saddle point characterization of efficient solutions for interval optimization problems

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Cited by 29 publications
(18 citation statements)
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“…Most often [4,14,32,37], IOPs have been analyzed with respect to a partial ordering [20]. Some researchers [3,11] used ordering relations of intervals based on the parametric comparison of intervals. In [7], an ordering relation of intervals is defined by a bijective correspondence between intervals and the points in R 2 .…”
Section: Literature Surveymentioning
confidence: 99%
See 1 more Smart Citation
“…Most often [4,14,32,37], IOPs have been analyzed with respect to a partial ordering [20]. Some researchers [3,11] used ordering relations of intervals based on the parametric comparison of intervals. In [7], an ordering relation of intervals is defined by a bijective correspondence between intervals and the points in R 2 .…”
Section: Literature Surveymentioning
confidence: 99%
“…In [7], an ordering relation of intervals is defined by a bijective correspondence between intervals and the points in R 2 . However, these ordering relations [3,11,7] of intervals can be derived from the relations described in [20]. Sengupta et al [30] proposed an acceptability function for intervals, just like a fuzzy membership function.…”
Section: Literature Surveymentioning
confidence: 99%
“…In the literature of IOP, there are various techniques and theorems for obtaining the solutions to IOPs (see [3,5,8,10,11,12,19,20,22,23,34]). Ishibuchi and Tanaka [19] proposed a method to solve linear IOPs, which is subsequently generalized in [7].…”
Section: Literature Surveymentioning
confidence: 99%
“…In 2016, Singh et al [33] proposed the concept of Pareto optimal solution for the interval-valued multi-objective programming problems. Many other researchers have also proposed optimality conditions and solution concepts for IOPs, see for instance [1,12,15,16,35] and the references therein.…”
Section: Introductionmentioning
confidence: 99%