Single item stochastic lot sizing problem considering capital flow and business overdraft

Zhen Chen, Roberto Rossi

Research output: Contribution to conferencePaperpeer-review

Abstract / Description of output

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 be-
low zero. A stochastic dynamic programming model maximizing expected -
nal capital increment is formulated to solve the problem to optimality. We
then investigate the performance of four controlling policies: (R;Q), (R; S),
(s; S) and (s, Q, S); for these policies, we adopt simulation-genetic algo-
rithm to obtain approximate values of the controlling parameters. Finally, a
simulation-optimization heuristic is also employed to solve this problem. Com-
putational comparisons among these approaches show that policy (s; S) and
policy (s; Q; S) 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.
Original languageEnglish
Number of pages5
Publication statusPublished - Aug 2017
Eventthe 8th International Workshop on Lot Sizing - Glasgow, United Kingdom
Duration: 23 Aug 201725 Aug 2017


Workshopthe 8th International Workshop on Lot Sizing
Abbreviated titleIWLS 2017
Country/TerritoryUnited Kingdom


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