A Decomposition Method to Optimize Concurrent Iterations Among Multiple Coupled Design Activities under Information Uncertainty.

DS 126: Proceedings of the 25th International DSM Conference (DSM 2023), Gothenburg, Sweden, October, 03 - 05, 2023

Year: 2023
Editor: Harold (Mike) Stowe; Tyson R. Browning; Steven D. Eppinger; Jakob Trauer; Christopher Langner; Matthias Kreimeyer; Ola Isaksson; Massimo Panarotto; Arindam Brahma
Author: Mohammad Khastehdel
Series: DSM
Institution: Amirkabir University of Technology, Islamic Republic of Iran
Page(s): 106-115
DOI number: 10.35199/dsm2023.12


In this paper, an algebraic partitioning method is proposed to make a trade-off between sequential and concurrent iterations among coupled activities. First, a proposed binary variable matrix named Iteration Transition Matrix (ITM) is developed to decouple multiple interdependent activities into a number of individual pairs. The innovative aspect of the ITM variable is its application in an Integer Linear Programming (ILP) model to build the equations of constraints which represents the required iterations to accomplish coupled activities. This model contributes to estimate unknown number of sequential iterations between each pair utilizing a stationary Markov Chain (MC). These estimated numbers are assumed to be used in equation of constraints in the ILP model. Finally, after establishing the objective function, the final results of the ILP represent optimum numbers of concurrent and sequential iterations. At the end, the developed model is applied in an example of an anti-corrosion tape product development process.

Keywords: Iteration Transition Matrix, Integer Linear Programming, Markov Chain, DSM


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