Designing the Customer Order Decoupling Point to Facilitate Mass Customization

Guo, Lin; Chen, Suhao; Allen, Janet K.; Mistree, Farrokh

doi:10.1115/detc2019-97379

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…For example, Wang et al proposed a joint optimization model considering both order allocation and CODP positioning under the mode of mass customization of logistics services [28]. Guo et al proposed a Formulation-Exploration method to make decisions on CODP positioning and improve the supply chain to support mass customization [34]. Liu proposed a determination method of optimal customization degree of the logistics service supply chain with mass customization service [35].…”

Section: Codp Positionmentioning

confidence: 99%

A Fuzzy Programming Model for Positioning Customer Order Decoupling Point Based on QFD in Logistics Service with Mass Customization

Wang

2020

Discrete Dynamics in Nature and Society

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Mass customization logistics service mode provides a new way to maintain the sustainable cooperative relationship between customers and integrators. One of the key factors to maintain the sustainable development of logistics service supply chain under MC mode is to locate a suitable customer order decoupling point (CODP) location. This paper investigates the problem of CODP in the logistics service supply chain based on the fuzzy set theory under the mass customization mode. With the help of a fuzzy QFD method and a new service quality function that we constructed, this paper quantifies the quality of a logistics service when the LSI selects a different CODP. Then, the fuzzy set of the high-quality logistics service and the fuzzy set of the satisfactory delivery time are built. Based on those two new fuzzy sets, this paper builds a new fuzzy programming model on CODP positioning. The solving methods of this model under different conditions are given. Finally, the influence of some important parameters on the optimal CODP position is studied by sensitivity analysis on a specific numerical case.

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Section: Codp Positionmentioning

confidence: 99%

A Fuzzy Programming Model for Positioning Customer Order Decoupling Point Based on QFD in Logistics Service with Mass Customization

Wang

2020

Discrete Dynamics in Nature and Society

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Adaptive Linear Programming Algorithm With Parameter Learning for Managing Engineering-Design Problems

Guo

Nellippallil

Smith

et al. 2020

Volume 11B: 46th Design Automation Conference (DAC)

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The adaptive linear programming (ALP) algorithm is an extension of the sequential linear programming algorithm where nonlinear formulations are iteratively approximated as linear formulations linearized about an iteration starting point. In the ALP algorithm, heuristics are used to determine the value of a critical parameter, namely, the reduced move coefficient (RMC). The RMC defines how far to move towards the solution of iteration “n” from the starting point for iteration “n” in specifying the starting point for iteration “n+1”. The RMC choice affects the efficacy of the approximation; however, there is no mechanism of evaluating the algorithm performance with respect to the RMC value so as to improve the design efficiency and effectiveness. This limitation is addressed in this paper. In this paper, we enhance the ALP algorithm with parameter learning (ALPPL) and generalize to make the knowledge gained reusable. We propose a three-step procedure of rule-based parameter learning leading to robust solutions. An industry-inspired problem, the integrated design of a hot rolling process chain for the production of a steel rod, is used to demonstrate the implementation. The three-step procedure could be used to improve other critical parameter determinations, especially when there is a lack of mechanisms for algorithm-performance evaluation, evaluation criteria vary with problems, or heuristics are over-used.

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Designing the Customer Order Decoupling Point to Facilitate Mass Customization

Cited by 2 publications

References 18 publications

A Fuzzy Programming Model for Positioning Customer Order Decoupling Point Based on QFD in Logistics Service with Mass Customization

A Fuzzy Programming Model for Positioning Customer Order Decoupling Point Based on QFD in Logistics Service with Mass Customization

Adaptive Linear Programming Algorithm With Parameter Learning for Managing Engineering-Design Problems

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