On an EOQ model with service level constraint under fuzzy-stochastic demand and variable lead-time

Rong, Mahendra; Maiti, Manoranjan

doi:10.1016/j.apm.2015.03.035

Cited by 16 publications

(5 citation statements)

References 20 publications

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“…Many scholars have only briefly processed the uncertain demand in the supply chain and researched this basis. Some researchers focused on manufacturing supply chain [17][18][19][20][21][22][23]. For example, the research by Rong et al [17] studied the inventory model with fuzzy stochastic demand, while Sadeghi et al [21] established a supplier inventory management model under uncertain demand constraints, under the area of fuzzy demand, and designed the cost allocation and quality control contract.…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers focused on manufacturing supply chain [17][18][19][20][21][22][23]. For example, the research by Rong et al [17] studied the inventory model with fuzzy stochastic demand, while Sadeghi et al [21] established a supplier inventory management model under uncertain demand constraints, under the area of fuzzy demand, and designed the cost allocation and quality control contract. Some other researchers concentrated on the perishable supply chain [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Demand-Profit Model for the Sustainable Development of Electric Vehicles in China from the Perspective of Three-Level Service Chain

Chen

Xing

et al. 2020

Sustainability

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Electric vehicles have great potential in dramatically reducing environmental pollution, which has become an important strategic direction for future sustainable development. With the influence of policy support and market, the construction of new energy supply infrastructure in China has achieved remarkable outcomes. However, according to the actual use of the new energy supply facilities, there is still a severe imbalance between long queues and unattended charging stations in some areas. Therefore, this paper aims to establish a fuzzy demand-profit model to accurately optimize new energy supply from the perspective of the three-level service chain. Then, based on authoritative historical sales data of electric vehicles in China in 2011–2018, the model is used to analyze the fuzzy demand for electric vehicle charging capacity. The research results indicate that the fuzzy demand-profit model is an effective tool to promote the coordination of new energy supply, which will provide support for the sustainable development of electric vehicles in China.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fuzzy Demand-Profit Model for the Sustainable Development of Electric Vehicles in China from the Perspective of Three-Level Service Chain

Chen

Xing

et al. 2020

Sustainability

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“…Wang et al (2015) [13] developed an EOQ model with imperfect quality items, and the time intervals are used as decision variables to simplify the objective function. Rong and Maiti (2015) [14] developed a practical EOQ inventory model with fuzzy stochastic demand because they considered a precise value of demand is not easy to predict. However, they considered the unsatisfied demand can be partially backordered under the constraint of a presetting service level.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic EPQ Model for Time-Varying Demand Problem With Product Life Cycle

Fang

Yeh

2020

IEEE Access

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The study explores a dynamic economic production quantity model whose demand function in consideration of market-trend issue to decide the optimal number of production cycles, the corresponding optimal production time points, and the best time to withdraw from the production line. The objective function of the total relevant costs considered in the model is formulated as a nonlinear programming problem, and a complete search procedure is developed to find the optimal solution of inventory cost. The characteristics of daily necessaries, technology products and fashion products are also analyzed to develop different strategies for the decision makers. The proposed model and algorithm not only provided the optimal solution of the production period and cycle time but also gave the suggestion of the best time to withdraw from the market. Moreover, in order to provide the managers with useful information of the impacts of inventory cost, Monte Carlo technique is used to simulate the stochastic demand. In considering of the stochastic demand, the situation of shortage will definitely happen without or insufficient safe stock. Finally, a numerical example and the corresponding sensitivity analyses are carried out to illustrate the features of our model by utilizing the search procedure developed in this study. INDEX TERMS inventory; economic production quantity; product life cycle; time-varying demand.

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“…Chang and Yeh [48], Sadeghu and Niaki [49], Lin et al [50], Cosgun et al [51], and Sadeghi et al [52] treated demand as a trapezoidal fuzzy number in their inventory models. Some other researchers including Rong and Maiti [53], Zhang et al [54], Moghaddam [55], and Huang et al [56] considered demand as a Triangular Fuzzy Number (TFN). In addition, Taleizadeh et al [57] presented a multi-constraint EOQ model with incremental discounts and uncertain item cost under fuzzy environment, and Jana et al [58] considered storage space and available budget as fuzzy variables.…”

Section: Introductionmentioning

confidence: 99%

Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand

2018

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Market conditions fluctuate abruptly in today’s competitive environment and leads to imprecise demand information. In particular, market demand data for freshly launched products is highly uncertain. Further, most of the products are generally manufactured through complex multi-stage production systems that may produce defective items once they enter the out-of-control state. Production management of a multi-stage production system in these circumstances requires robust production model to reduce system costs. In this context, this paper introduces an imperfect multi-stage production model with the consideration of defective proportion in the production process and uncertain product demand. Fuzzy theory is applied to handle the uncertainty in demand information and the center of gravity approach is utilized to defuzzify the objective function. This defuzzified cost objective is solved through the analytical optimization technique and closed form solution of optimal lot size and minimum cost function are obtained. Model analysis verifies that it has successfully achieved global optimal results. Numerical experiment comprising of three examples is conducted and optimal results are analyzed through sensitivity analysis. Results demonstrate that larger lot sizes are profitable as the system moves towards a higher number of stages. Sensitivity analysis indicates that the processing cost is the most influencing factor on the system cost function.

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On an EOQ model with service level constraint under fuzzy-stochastic demand and variable lead-time

Cited by 16 publications

References 20 publications

A Fuzzy Demand-Profit Model for the Sustainable Development of Electric Vehicles in China from the Perspective of Three-Level Service Chain

A Fuzzy Demand-Profit Model for the Sustainable Development of Electric Vehicles in China from the Perspective of Three-Level Service Chain

A Dynamic EPQ Model for Time-Varying Demand Problem With Product Life Cycle

Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand

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