This paper presents an integrated production-inventory model where a vendor produces an item in a batch production environment and supplies it to a set of buyers. The buyer level demand is assumed to ...be independent normally distributed and lead time of every buyer can be reduced at an added crash cost. The buyers review their inventory using continuous review policy, and the unsatisfied demand at the buyers is completely backordered. A model is formulated to minimize the joint total expected cost of the vendor–buyers system to determine the optimal production-inventory policy. Since it is often difficult to estimate the stock-out cost in inventory systems, and so instead of having stock-out cost component in the objective function, a service level constraint (SLC) corresponding to each buyer is included in the model. A Lagrangian multiplier technique based algorithmic approach is proposed, which evaluates a very limited number of combinations of lead time of the buyers to find simultaneously the optimal lead time, order quantity and safety factor of the buyers and the number of shipments between the vendor and the buyers in a production cycle. Finally, a numerical example and effects of the key parameters are included to illustrate the results of the proposed model.
The purpose of this paper is to model dynamic feedback effects and complex interactions among risks affecting foodgrains transportation using a system dynamics approach. The risk scenario is ...simulated using a system dynamics model considering risk index values. It has been observed that there is a significant increase in inventory level from 8.39% to 28.4% and vehicle capacity from 8.99% to 28.4% with a change in risk value by 30%. This can help managers to develop inventory and transportation policies. It will, therefore, help to generate risk reduction scenarios for better availability of foodgrains through integrated risk control and mitigation in a supply chain. The key findings drawn for transportation and inventory management of foodgrains will help policy-makers to improve the efficiency of foodgrains supply chain. This research uniquely analyses the dynamic implication of inventory-transportation policies on foodgrains transportation system using system dynamics modelling approach.
PurposeThis paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.Design/methodology/approachThis paper used ...failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.FindingsThe findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.Practical implicationsThe outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.Originality/valueSpecifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.
Dynamic pricing is a crucial revenue management technique when product status changes over time. It can become more prominent if applied in conjunction with an inventory management strategy for ...deteriorating items. This paper presents a framework for dynamic pricing in a continuous time horizon for a dual-channel supply chain consisting of a manufacturer and a retailer. The manufacturer produces a deteriorating product and sells through direct and indirect retail channels, and both channels compete with each other over retail prices. The freshness of the product varies with time, and thus both channels invest in preservation technology, which further leads to carbon emissions. We derive an analytical solution to the dual-channel pricing model. Furthermore, the case of single-channel pricing has been investigated to study and compare its pricing strategy with the dual-channel pricing strategy. Lastly, a numerical illustration is presented to study the impact of key parameters on optimal decisions through sensitivity analysis. We provide managerial recommendations in various scenarios like an increase in competition, the shift of consumer preference between channels and fluctuation in demand.
Purpose This paper investigates the overall system risk for a foodgrains supply chain capturing the interrelationship among the risk factors and the effect of risk mitigation strategies. ...Design/methodology/approach This paper first calculates the weight of risk factors using an integrated approach of failure mode, effects analysis and fuzzy VIKOR technique. Next, the weights are utilized as input for the weighted fuzzy Petri-net (WFPN) approach to calculate the system risk. Findings Two different WFPN models are developed based on the relationships among the risk factors, and both models demonstrate a higher risk value for the overall system. Originality/value The proposed methodology will help practitioners or managers understand the complexity involved in the system by capturing the interrelationship behaviour. This study also considers the concurrent effect of risk mitigation strategies for calculating the overall system risk, which helps to improve the system’s performance.
This paper considers a two-echelon supply chain inventory problem consisting of a single-vendor and a single-buyer. In the system under study, a vendor produces a product in a batch production ...environment and supplies it to a buyer facing a stochastic demand, which is assumed to be normally distributed. Also, buyer’s lead time is controllable which can be shortened at an added cost and all shortages are backordered. A model has been formulated for an integrated vendor–buyer problem to jointly determine the optimal order quantity, lead time and the number of shipments from the vendor to the buyer during a production cycle while minimizing the total expected cost of the vendor–buyer integrated system. It is often difficult to estimate the shortage cost in inventory systems. Therefore, instead of having a shortage cost term in the objective function, a service level constraint (SLC) is included in the model that requires a certain proportion of demands to be met in each cycle. An efficient procedure has been suggested to find the bounds on number of shipments and then, an algorithm is developed to obtain the optimal solution of the proposed model. A numerical example is included to illustrate the algorithmic procedure and the effects of key parameters are studied to analyze the behavior of the model. Finally, the savings of buyer and vendor are investigated from implementation of joint optimization model over the model in which they minimize their own cost independently.
This paper presents a centralized production-inventory model for an infinite planning horizon of a two-echelon closed-loop supply chain (CLSC) consisting a retailer, manufacturer, and remanufacturer. ...The demand at the retailer is satisfied through the new and remanufactured products received from the manufacturer and remanufacturer, respectively. The proposed model considers demand at the retailer and return at the remanufacturer as random. The manufacturer and remanufacturer produce the products at a finite rate, and they deliver to the retailer alternatively in multiple batches. An algorithm is developed to find the optimal-lot sizing and shipment policies of each entity of the CLSC by minimizing the expected joint total cost of the system. The results show that the CLSC is more profitable than the forward supply chain when the remanufacturing cost of the returned product is significantly low compared to the manufacturing cost of the new product, the demand variation at the retailer is low, and the fraction of demand returned is close to 1.
Black cotton soils are expansive soils which exhibit high swelling and shrinking when exposed to changes in moisture content. Durability of structure resting on expansive clays is always in question ...due to swelling/shrinkage of such clays. The performance of paved and unpaved road pavements constructed over such expansive soil subgrades is often poor and in most cases show cracking, potholes, wheel path rutting, serious differential settlements and heaving in various locations. In addition to problems related to expansive soils another problem arising in all developing and developed countries is due to the wastes generated from various activities which not only cause severe environmental problems, but also occupy a huge area of land for its disposal. Rice husk ash (RHA) is one such wastes produced from the burning of rice husk and if used as an additive to expansive soil shall not only significantly reduce the swelling/shrinkage characteristics of such soils but also solve the environmental and disposal problems being created by the ash. The paper presents the results of an experimental investigation conducted to study the effect of RHA on swelling, shrinkage and compaction characteristics of the expansive soil. The RHA was mixed with expansive soil in varying proportions. Free swell index, Atterberg limits, light compaction tests, unconsolidated undrained triaxial compression tests, California bearing ratio tests were carried out with specimens containing varying percentages of RHA. It is concluded that addition of RHA in appropriate proportions not only reduces the swelling and shrinkage behavior of expansive soil significantly but also makes it more stable.
Humanitarian aid agencies usually resort to inventory prepositioning to mitigate the impact of disasters by sending emergency supplies to the affected area as quickly as possible. However, a lack of ...replenishment opportunity after a disaster can greatly hamper the effectiveness of the relief operation due to uncertainty in demand. In this paper, a prepositioning problem is formulated as a two-period newsvendor model where the response phase is divided into two periods. The model acknowledges the demand to be uncertain even after the disaster and utilises the Bayesian approach to revise the demand of the second period. Based on the revised demand, an order is placed at the beginning of the second period to be replenished instantaneously. A two-stage solution methodology is proposed to find the prepositioning quantity and post-disaster replenishment quantity, which minimise the total expected costs of relief operations. A numerical example is presented to demonstrate the solution methodology, and sensitivity analysis is performed to examine the effect of model parameters. The results highlight the indifferent characteristics shown by the replenishment quantity with the variation in model parameters.
•Modelling prepositioning with a post-disaster replenishment as a two-period newsvendor approach.•The model acknowledges the demand to be uncertain even after the disaster.•Incorporates Bayesian approach to revise the demand distribution.•Proposes a two-stage solution methodology to determine prepositioning quantity and post-disaster replenishment quantity.
•Develop model for a supply chain considering strict carbon cap policy.•Conceive stochastic demand for this model.•Both backorder and lost sales have been considered.•Major sources of emission and ...cost are taken into account.•Offer managerial insights with numerical examples and sensitivity analysis.
Due to stringent laws and increasing awareness of customers, organizations are becoming environmental conscious and looking beyond conventional cost minimization/profit maximization approach and striving to curb carbon emission. In this article, we have considered strict carbon cap policy to determine the optimal order quantity, reorder point and number of shipments in a two-echelon supply chain under stochastic demand considering partial backorders. All the major sources of emission such as production, inventory, and transportation have been considered. The objective is to minimize the total expected supply chain cost while satisfying the carbon emission constraint. A numerical example is given to illustrate the solution procedure. Further, sensitivity analyses have been carried out to get insight that how with operational adjustments both cost and emission can be controlled.
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