Optimizing an Imperfect Production Model with Varying Setup Cost, Price Discount, and Lead Time Under Fuzzy Demand

Karthick, B.; Uthayakumar, R.

doi:10.1007/s41660-020-00133-8

Cited by 16 publications

(6 citation statements)

References 37 publications

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“…Primarily in this model, we assume that the production process is perfect, so it can be extended by turning this model into an imperfect production process. Another extension is possible by relaxing the equal-sized shipment and fixed demand rate in the proposed model (refer, Yu and Hsu [38] (2017), Ganguly et al [13] (2019) and Ganesh Kumar and Uthayakumar [11] (2019) for unequal-sized shipments, Sarkar et al [31] (2020) for price and advertisement-dependent demand, Karthick and Uthayakumar [20] (2021), [21] (2021) for fuzzy demand). Exploring the changes that occur in this model by combining concepts such as learning and forgetting can be considered an extension (refer, Giri and Masanta [14]).…”

Section: Discussionmentioning

confidence: 99%

“…Sarkar et al [31] (2020) suggested the supply chain model by assuming the inventory associated cost as a triangular fuzzy number under the signed distance method. Karthick and Uthayakumar [20] (2021) investigated the imperfect production inventory model with triangular fuzzy demand under the signed distance method. Karthick and Uthayakumar [21] (2021) developed a VMI-consignment stock policy model with multiple items and trapezoidal fuzzy number under the graded mean integration method.…”

Section: Delay In Shipmentmentioning

confidence: 99%

“…fuzzy or vague terms, to express their preferences. Thus, the solution to these sorts of challenges can be found by considering an uncertain parameter with fuzzy numbers (see for instance, [20][21][22]). Generally, fuzzy numbers are used to treat uncertain parameters.…”

Section: Introductionmentioning

confidence: 99%

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A single-consignor multi-consignee multi-item model with permissible payment delay, delayed shipment and variable lead time under consignment stock policy

Karthick

Uthayakumar

2021

RAIRO-Oper. Res.

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This article proposes a two-level fuzzy supply chain inventory model, in which a single consignor delivers multiple items to the multiple consignees with the consignment stock agreement. The lead time is incorporated into the model and is considered a variable for obtaining optimal replenishment decisions. In addition, crashing cost is employed to reduce the lead time duration. This article investigates four different cases under controllable lead time to analyze the best strategy, focusing on two delays such as delay-in-payments and delay-in-shipment. In all four cases, all associated inventory costs are treated as a trapezoidal fuzzy number, and a signed distance method is employed to defuzzify the fuzzy inventory cost. An efficient optimization technique is adopted to find the optimal solution for the supply chain. Four numerical experiments are conducted to illustrate the four cases. Any one of these experimental results will provide the best solution for the ideal performance of the business under controllable lead time in the consignment stock policy. Finally, the managerial insights, conclusion and future direction of this model are provided.

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Section: Discussionmentioning

confidence: 99%

Section: Delay In Shipmentmentioning

confidence: 99%

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A single-consignor multi-consignee multi-item model with permissible payment delay, delayed shipment and variable lead time under consignment stock policy

Karthick

Uthayakumar

2021

RAIRO-Oper. Res.

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“…Sarkar et al [31] have developed a three-level supply chain model with fuzzy inventory cost under the signed distance defuzzification method. Karthick and Uthayakumar [18] examined the two-level supply chain model with triangular fuzzy demand under the signed distance defuzzification approach. Karthick and Uthayakumar [19] analyzed the effects of constant and trapezoidal fuzzy demand under VMI-CS policy.…”

Section: Cs Policy In Fuzzy Environmentmentioning

confidence: 99%

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

Karthick

Uthayakumar

2022

Complex Intell. Syst.

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This paper considers a dual-channel supply chain with one vendor and multiple buyers in which (1) one channel is an offline channel where standard products are produced and shipped to the buyers and (2) the second channel is an online channel with the flow of customized products between the vendor and the online buyers/consumers. The first channel follows a vendor managed inventory with consignment stock (VMI-CS) agreement between the vendor and buyers. The supply lead time between the vendor and the buyer is considered controllable, at a cost. Two models are analyzed: (1) in the first model, the standard and customized product’s demand rate is assumed to be price and lead time-sensitive, and (2) in the second model, the demands are uncertain or ambiguous and are treated as a trapezoidal fuzzy number. It is reasonably complex to obtain analytical solutions. Hence, two algorithms are proposed to obtain the numerical solution with the objective of maximizing total profit. Numerical examples, sensitivity analysis, and managerial insights are given to test the model. Finally, conclusions and directions for future research are provided.

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“…They explored and quantified the benefits of lead-time reduction for commonly used lot size quantity, production rate, safety factor, reorder point, advertisement cost and vendor's setup cost. Karthick and Uthayakumar (2021) considered a two-level integrated vendor-buyer supply chain model that is developed in a fuzzy environment [42]. They investigated the imperfection in the production process with ambiguous demand, reworking, and setup cost reduction under a controllable lead-time.…”

Section: Introductionmentioning

confidence: 99%

Coordination of a single-supplier multi-retailer supply chain via joint ordering policy considering incentives for retailers and utilizing economies of scale

Seifbarghy,

Shoeib,

Pishva

2022

Scientia Iranica

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Lead-time fluctuations cause a low supply chain service level through increasing stock-outs. Lack of the supplier's awareness of the retailers' ordering policy is one of the main reasons for the lead-time fluctuations. In this paper, a twoechelon supply chain including single supplier, multiple retailers is studied under two scenarios of decentralized and centralized decision-making. In the first scenario, each retailer independently uses a continuous review inventory policy and the supplier does not know when each retailer will order. This policy prolongs order fulfillment by the supplier and increases order-processing costs. In the second scenario, retailers are encouraged to enter into a joint cooperation plan and change their ordering policy from independent continuous review policies to a joint periodic review policy. In this case, the supply chain can utilize the benefits of economies of scale via integrating and shipping several retailers' orders. The study also determines range of the acceptable lead-time reduction by supplier and retailers for participating in the joint cooperation plan. The results show that joint cooperation plan creates more benefits for the supply chain in terms of cost and service level.

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Optimizing an Imperfect Production Model with Varying Setup Cost, Price Discount, and Lead Time Under Fuzzy Demand

Cited by 16 publications

References 37 publications

A single-consignor multi-consignee multi-item model with permissible payment delay, delayed shipment and variable lead time under consignment stock policy

A single-consignor multi-consignee multi-item model with permissible payment delay, delayed shipment and variable lead time under consignment stock policy

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

Coordination of a single-supplier multi-retailer supply chain via joint ordering policy considering incentives for retailers and utilizing economies of scale

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