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Single item stochastic lot sizing problem considering capital flow and business overdraft
This paper introduces capital flow to the single item stochastic lot sizing
problem. A retailer can leverage business overdraft to deal with unexpected
capital shortage, but needs to pay interest if its available balance goes below
zero. A stochastic dynamic programming model maximizing expected final capital
increment is formulated to solve the problem to optimality. We then investigate
the performance of four controlling policies: (), (), () and
(, , ); for these policies, we adopt simulation-genetic
algorithm to obtain approximate values of the controlling parameters. Finally,
a simulation-optimization heuristic is also employed to solve this problem.
Computational comparisons among these approaches show that policy and
policy provide performance close to that of optimal
solutions obtained by stochastic dynamic programming, while
simulation-optimization heuristic offers advantages in terms of computational
efficiency. Our numerical tests also show that capital availability as well as
business overdraft interest rate can substantially affect the retailer's
optimal lot sizing decisions.Comment: 18 pages, 3 figure
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