Multi-objective vendor managed inventory system with interval type-2 fuzzy demand and order quantities

Ashraf, Zubair; Shahid, Mohammad

doi:10.1108/ijicc-12-2020-0212

Cited by 6 publications

(3 citation statements)

References 51 publications

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“…A robust single fuzzifier IT2 fuzzy C-means clustering method to adopt the interval-valued numbers for the application of land cover segmentation was presented by Wu and Gao [27]. Ashraf and shahid [28] established the multiobjective vender managed model with IT2FNs for demand and order quantity. Javanmard et al [29] demonstrated a fuzzy solution to a linear programming problem where all coefficients are understood by IT2 FNs.…”

Section: A Interval Type-2 Fuzzy Set and Applicationsmentioning

confidence: 99%

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

et al. 2023

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Multi-objective reliability-redundancy allocation problem (MORRAP) needs to maximize system reliability and minimize cost, weight, and volume with underlining constraints. In the systems' design and analysis phase, uncertainties can occur from various sources, such as manufacturing variability, environmental conditions, user behavior, etc. To deal with this, we present a generalization of the traditional MORRAP under multiple empirical and ambiguous circumstances, named interval type-2 fuzzy multiobjective reliability redundancy allocation problem (IT2FMORRAP). The newly formulated IT2FMORRAP considers optimizing goals as reliability, cost, and weight for a series-parallel system with interval type-2 fuzzy number. The mathematical formulation is established under which the proposed IT2FMORRAP model reduces to T1FMORRAP (type-1 fuzzy MORRAP), IVMORRAP (interval-valued MORRAP), and classical MORRAP. An Enhanced Karnik-Mendel and NSGA-II algorithm-based solving strategy is developed for the proposed IT2FMORRAP. The real-world dataset is considered to demonstrate the efficacy of the solution method for the proposed problem. A Kmean clustering technique identifies the best solution sets from the knee region of the generated Pareto fronts. An experimental study on commonly used performance metrics reveals that IT2FMORRAP performs significantly better than T1FMORRAP and crisp MORRAP. Further, the statistical analysis also confirms the hypothesis established in the empirical research. Finally, a comparative performance study has been conducted with notable state-of-the-art papers from the literature to encounter an appropriate establishment for the proposed work in the domain.

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Section: A Interval Type-2 Fuzzy Set and Applicationsmentioning

confidence: 99%

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

et al. 2023

Self Cite

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“…They used Imperialist Competitive Algorithm (ICA) to solve the model. Ashraf and Shahid (2021) suggested a multiobjective VMI system with interval type-2 fuzzy demand and order quantities. They applied NSGA-II with EKM (Enhanced Karnink-Mendel) algorithm.…”

Section: Application Of Vmi In Scmentioning

confidence: 99%

Viable supply chain with vendor-managed inventory approach by considering blockchain, risk and robustness

et al. 2022

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This research shows a Viable Supply Chain with Vendor Managed Inventory approach by considering Blockchain, Risk, and Robustness. We embedded Blockchain Technology (BCT) to improve SC agility. To tackle risk and robustness, we suggest a new objective function with the weighted expected value, worst case, and Entropic Value at Risk for considering risk and robustness under different scenarios. This model is Mixed-Integer Linear Programming, and GAMS-Bonmin is utilized to solve it. The case study of this research is on the Pharmacy industry. We compare problems in the situation with BCT and without BCT. The results show that the cost function of the main problem without BCT is greater than the same problem with BCT, and its gaps are 0.61%. Finally, the cost function increase by increasing the conservative coefficient and decreasing the resiliency coefficient. The cost function reduces by increasing the confidence level. We change the scale of the problem and define problems. By increasing the scale of the problem, the solution time increased. KeywordsViable supply chain • Vendor managed inventory • Blockchain • Risk • Robustness B Reza Lotfi

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“…By restricting the number of features considered at each split, the base estimators are forced to make more independent decisions, which can lead to a more robust The BBC combines the advantages of bagging and sampling techniques to address the issue of imbalanced datasets [20]. Several researchers in recent times and the past have recommended fuzzy logic (e.g., [11], [20], [21], [22], [23], [24], [25]). The objective is to add human-centric design along with advanced machine-learning algorithms.…”

Section: Modeling and Evaluationmentioning

confidence: 99%

Backorder Prediction in Inventory Management: Classification Techniques and Cost Considerations

Maitra,

Kundu

2022

ECTI-CIT Transactions

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This article introduces an advanced analytical approach for predicting backorders in inventory management. Backorder refers to an order that cannot fulfilled immediately due to stock depletion. Multiple classification techniques, including Balanced Bagging classifiers, Fuzzy Logic, Variational Autoencoder (VAE) - Generative Adversarial Networks, and Multilayer Perceptron classifiers, are assessed in this work using performance evaluation metrics such as ROC-AUC and PR-AUC. Moreover, this work incorporates a profit function and misclassification costs, considering the financial implications and costs associated with inventory management and backorder handling. The study suggests a hybrid modelling approach, which includes ensemble techniques and VAE, which effectively addresses imbalanced datasets in inventory management. This approach emphasizes interpretability and reduces false positives and false negatives. This research contributes to the advancement of predictive analytics and offers valuable insights for future investigations in backorder forecasting and inventory control optimization for decision-making.

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Multi-objective vendor managed inventory system with interval type-2 fuzzy demand and order quantities

Cited by 6 publications

References 51 publications

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

Viable supply chain with vendor-managed inventory approach by considering blockchain, risk and robustness

Backorder Prediction in Inventory Management: Classification Techniques and Cost Considerations

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