Multiple-Square-Root Minimization Problem ()
ABSTRACT
The Multiple-Square-Root
Minimization Problem (MSR) has an objective function that consists of a sum of
a linear term and at least two square root terms. The Lagrangian sub-problem for the LMRP is a typical MSR problem and
there are other MSR problems in real life. A simple example is that we add
other concave costs besides the safety stock cost to the LMRP, such as the labor cost and even
minimize the negation of the revenue. We tested a sort of heuristic involved,
similar to the method to solve the problem of the LMRP vibrational days, and we
explore the heuristic is probably the most optimal condition. The accuracy of this
approach is declining at a slow rate, because the number of square roots is
increasing, and when the number is not too large, it stays at a higher level.
Share and Cite:
Zhang, X. , Tian, X. , Wang, C. and Li, T. (2017) Multiple-Square-Root Minimization Problem.
American Journal of Industrial and Business Management,
7, 927-943. doi:
10.4236/ajibm.2017.77066.
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