Content deleted Content added
→References: {{cite article|last1=Kruk|first1=Serge|last2=Wolkowicz|first2=Henry|title=Pseudolinear programming|url=http://www.jstor.org/stable/2653207|journal=SIAM Review|volume=41 |year=1999 |
Fractional-linear programs are convex minimization problems with a special property, pseudoconvexity. In some cases, for example in some scheduling algorithms, FLPs can be solved by a variant of t |
||
Line 4:
For example, if in the frame of LP we maximize '''profit = income − cost''' and obtain maximal profit of 100 units (= $1100 of income − 1000$ of cost), then using LFP we can obtain only $10 of profit which requires only $50 of investment. Thus, in LP we have efficiency $100/$1000 = 0.1, at the same time LFP provides efficiency equal to $10/$50 = 0.2.
Fractional-linear programs are [[convex minimization]] problems with a special property, pseudoconvexity. In some cases, for example in some scheduling algorithms, FLPs can be solved by a variant of the [[simplex algorithm]] (of [[George Dantig]]).<ref>Source1
</ref><ref>Source2</ref>
== References ==
| |||