M
Mohammad Saber Fallah Nezhad
Researcher at Yazd University
Publications - 52
Citations - 422
Mohammad Saber Fallah Nezhad is an academic researcher from Yazd University. The author has contributed to research in topics: Acceptance sampling & Sampling (statistics). The author has an hindex of 9, co-authored 47 publications receiving 323 citations. Previous affiliations of Mohammad Saber Fallah Nezhad include Sharif University of Technology.
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A new monitoring design for uni-variate statistical quality control charts
TL;DR: The simulation results show that the proposed methodology performs better than other charts for all of the examined shift scenarios and for an autocorrelated AR(1) process, the performance of the proposed control chart compared to the other existing residual-based control charts turns out to be promising.
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A joint supplier selection and order allocation model with disruption risks in centralized supply chain
Elham Esmaeili-Najafabadi,Mohammad Saber Fallah Nezhad,Hamid Pourmohammadi,Mahboobeh Honarvar,Mohammad Ali Vahdatzad +4 more
TL;DR: In this paper, a mixed-integer nonlinear programming model is presented to optimize supplier selection and order allocation simultaneously in centralized supply chains considering disruption risks, and two protective policies are taken into account.
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Repetitive group sampling plan based on the process capability index for the lot acceptance problem
TL;DR: In this article, a repetitive group sampling (RGS) plan based on process capability indices (PCI) is introduced for variables' inspection, and the optimal parameters of the developed RGS plan are obtained considering constraints related to the risk of consumers and producers.
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A New Acceptance Sampling Policy Based on Number of Successive Conforming Items
TL;DR: In this paper, the authors developed an optimization model to determine the optimum values of the thresholds such that constraints on the probability of Type I and Type II errors are satisfied, where the expected total cost of the inspection problem containing the costs of acceptance, rejection, and inspection was derived.
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Risk-averse supplier selection and order allocation in the centralized supply chains under disruption risks
TL;DR: A mixed-integer non-linear programming model for the integrated supplier selection and order allocation in a centralized supply chain considering the disruption risks and a risk-averse decision-maker is proposed and the particle swarm optimization (PSO) algorithm is applied as the solution approach.