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A mathematical programming-based solution method for the nonstationary inventory problem under correlated demand
Tarim, S. Armagan
This paper extends the single-item single-stocking location nonstationary stochastic inventory problem to relax the assumption of independent demand. We present a mathematical programming-based solution method built upon an existing piecewise linear approximation strategy under the receding horizon control framework. Our method can be implemented by leveraging off-the-shelf mixed-integer linear programming solvers. It can tackle demand under various assumptions: the multivariate normal distribution, a collection of time-series processes, and the Martingale Model of Forecast Evolution. We compare against exact solutions obtained via stochastic dynamic programming to demonstrate that our method leads to near-optimal plans.
Inventory , Correlated demand , Stochastic programming , Mixed integer linear programming , Martingale model of forecast evolution
Xiang, M., Rossi, R., Martin-Barragan, B. and Tarim, S. A. (2022) 'A mathematical programming-based solution method for the nonstationary inventory problem under correlated demand', European Journal of Operational Research. doi: 10.1016/j.ejor.2022.04.011