MATEC Web of Conferences
Volume 51, 20162016 International Conference on Mechanical, Manufacturing, Modeling and Mechatronics (IC4M 2016)
|Number of page(s)||6|
|Section||Chapter 1: Engineering Simulation, Modelling and Analytical Studies|
|Published online||06 April 2016|
A Scenario Tree based Stochastic Programming Approach for Multi-Stage Weapon Equipment Mix Production Planning in Defense Manufacturing
1 Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, 410073, P. R. China
2 School of Materiel Management and Safety Engineering, Air Force Engineering University, Xi’an 710051, P. R. China
3 State Key Laboratory of Complex System Simulation, Beijing Institute of System Engineering, Beijing, 100101, P. R. China
a Corresponding author: email@example.com
The evolving military capability requirements (CRs) must be meted continuously by the multi-stage weapon equipment mix production planning (MWEMPP). Meanwhile, the CRs possess complex uncertainties with the variant military tasks in the whole planning horizon. The mean-value deterministic programming technique is difficult to deal with the multi-period and multi-level uncertain decision-making problem in MWEMPP. Therefore, a multi-stage stochastic programming approach is proposed to solve this problem. This approach first uses the scenario tree to quantitatively describe the bi-level uncertainty of the time and quantity of the CRs, and then build the whole off-line planning alternatives assembles for each possible scenario, at last the optimal planning alternative is selected on-line to flexibly encounter the real scenario in each period. A case is studied to validate the proposed approach. The results confirm that the proposed approach can better hedge against each scenario of the CRs than the traditional mean-value deterministic technique.
© Owned by the authors, published by EDP Sciences, 2016
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