Optimal ordering policy with non- increasing demand for time dependent deterioration under fixed life time production and permissible delay in payments

Most of the items in the universe deteriorate over time. Many items such as pharmaceuticals, high tech products and readymade food products also have their expiration dates. This paper developes an economic order quantity model for retailer in which demand rate is linearly time dependent and non increasing function of time, deterioration rate is time dependent having expiration dates under trade credits..We then show that the total average cost is sensitive with respect to the key parameters. Furthermore, we discuss several sub- special cases. Finally, numerical examples and sensitivity analysis is provided to illustrate the results. Mathematica 5.2 software is used to find numerical results

A sustainable game strategic supply chain model with multi-factor dependent demand and mark-up under revenue sharing contract

Abstract In the current socio-economic situation, the daily demand for essential goods in the business sector is always changing owing to various unavoidable reasons. Choosing the right method for a profitable business has become quite tricky. The proposed study introduces different business strategies based on trade credit, revenue sharing contract, variable demand and production rate. As trade credit is one of the best policies to attract customers, there are two types of models based on it. In the first model, demand depends on average selling price, green degree, and products quality. An additional trade-credit factor is in the second model. However, considering coordination, non-coordination, and revenue sharing contracts, each model has three sub-cases. The main aim is to find the best strategy for the profit maximization of the supply chain members. Green investment, maintenance, and multi-factor dependent demand make the model more sustainable. The global optimization is established theoretically and different propositions are developed. Through numerical experiments, the global optimality is also verified. Some special cases, with a comparative graph, are provided for the validation of these results and to find the best strategy for profit maximization. Finally, some concluding remarks along with future extensions are discussed

Greening the Supply Chain with Reworked Items

Abstract In the Last few decades, realization about environment has given considerable attention to produce green Products in all fields worldwide. Along with producing green, reuse and recycle of used products also has been promoted to save the environment as much as possible. Though every industry is following its own way to implement green up to certain level but electronics industry is equally forcing reuse and recycle of used products to reduce the e-waste which is increasing at a high-speed due to small life cycle and tough to dump because of its toxic and hazardous nature, which further effects the environment safety. In this paper it has been explored how the forward-reverse supply chain model is decisive to the success of greening the products, specifically focusing on the life cycle cost, and effective cost and profit analysis by calculating total integrated profit function which reduces life cycle cost and satisfies customer requirements for a given period of time. The consequential of this study can be helpful to implement the GSCM concept in electronics Industry and final ratios of integrated profit can be improved by using reworked or reused products, simultaneously reducing the cost of products, in between supplier and buyer

Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand

The advertising of any smart product is crucial in generating customer demand, along with reducing sale prices. Naturally, a decrease in price always increases the demand for any smart product. This study introduces a multi-product production process, taking into consideration the advertising- and price-dependent demands of products, where the failure rate of the production system is reduced under the optimum energy consumption. For long-run production systems, unusual energy consumption and machine failures occur frequently, which are reduced in this study. All costs related with the production system are included in the optimum energy costs. The unit production cost is dependent on the production rate of the machine and its failure rate. The aim of this study is to obtain the optimum profit with a reduced failure rate, under the optimum advertising costs and the optimum sale price. The total profit of the model becomes a complex, non-linear function, with respect to the decision variables. For this reason, the model is solved numerically by an iterative method. However, the global optimality is proved numerically, by using the Hessian matrix. The numerical results obtained show that for smart production, the maximum profit always occurs at the optimum values of the decision variables

A supply chain model with service level constraints and strategies under uncertainty

In the current socio-economic situation, the daily demand for essential goods in the business sector is always changing owing to various unavoidable reasons. As a result, choosing the right method for profitable business has become quite tricky. This study introduces different business strategies based on constant and fuzzy demands. There are two types of constraints considered in this model to avoid the backorder cost. However, combining the service-level constraints with the constant and fuzzy demand, this study compares the total costs, and finally, the best strategy is established. Moreover, investing a small amount, this model improves the quality of the products and reduces the vendor’s setup cost. Depending on the number of transported products, this model follows the transportation discount policy for hassle-free delivery of the products with a minimum delivery rate. The Kuhn-Tucker optimization technique is employed, and global optimality is verified numerically, analytically using the Hessian matrix. This model’s robustness is discussed through a comparative study, numerical examples, sensitivity analysis, graphical representation, and managerial insights. Finally, some concluding remarks along with future extensions are discussed

Supply chain models with imperfect quality items when end demand is sensitive to price and marketing expenditure

This paper studies supply chain model for imperfect quality items under which unit price and unit marketing expenditure imposed by the buyer, regulates the demand of the item. It is presumed that with the accustomed supply chain model, all produced items are of good quality, coincidentally, it engrosses some percentage of defective items. Thus, inspection process becomes essential for the buyer to segregate the defective items, which are then sold at discounted price at the end of the screening process. In this paper, a supply chain model is ensued to substantiate the interaction and democracy of the participants in the supply chain, the buyer and seller, is pitched by non-cooperative and cooperative game theoretical approaches. In the non-cooperative method, the Stackelberg game approach is used in which one player behaves as a leader and another one as a follower. The co-operative game approach is based on a Pareto efficient solution concept, in which both the players work together to enhance their profit. Lastly, to demonstrate the significance of the theory of the paper, numerical examples including sensitivity analysis are presented

Loss profit estimation using association rule mining with clustering

Data mining is the technique to find hidden patterns from a very large volume of historical data. Association rule is a type of data mining that correlates one set of items or events with another set of items or events. Another data mining strategy is clustering technique. This technique is used to create partitions so that all members of each set are similar according to a specified set of metrics. Both the association rule mining and clustering helps in more effective individual and group decision making for optimal inventory control. Owing to the above facts, association rules are mined from each cluster to find frequent items and then loss profit is calculated for each frequent item. Initially, the clustering algorithm is used to partition the transactional database into different clusters. Apriori, a classic data mining algorithm is utilized for mining association rules from each cluster to find frequent items. Later the loss profit is calculated for each frequent item. The obtained loss profit is used to rank frequent items in each cluster. Thus, the ranking of frequent items in each cluster using the proposed approach greatly facilitate optimal inventory control. An example is illustrated to validate the results

How Does a Radio Frequency Identification Optimize the Profit in an Unreliable Supply Chain Management?

Competition in business is higher in the electronics sector compared to other sectors. In such a situation, the role of a manufacturer is to manage the inventory properly with optimized profit. However, the problem of unreliability within buyers still exists in real world scenarios. The manufacturer adopts the radio frequency identification (RFID) technology to manage the inventory, which can control the unreliability, the inventory pooling effect, and the investment on human labor. For detecting RFID tags, a reasonable number of readers are needed. This study investigates the optimum distance between any two readers when using the optimum number of readers. As a vendor managed inventory (VMI) policy is utilized by the manufacturer, a revenue sharing contract is adopted to prevent the loss of buyers. The aim of this study is to maximize the profits of a two-echelon supply chain management under an advanced technology system. As the life of electronic gadgets is random, it may not follow any specific type of distribution function. The distribution-free approach helps to solve this issue when the mean and the standard deviation are known. The Kuhn-Tucker methodology and classical optimization are used to find the global optimum solution. The numerical analysis demonstrates that the manufacturer can earn more profit in coordination case after utilizing revenue sharing and the optimum distance between readers optimizing cost related to the RFID system. Sensitivity analysis is performed to check the sensibility of the parameters

Payment policy for a three-echelon supply chain management under advertisement-driven demand

Payment and selling are two important policies for a supply chain management. All participating supply chain players can earn profit based on the successful implementation of these two policies. The payment policy provides buyers with some extra time to pay for the product. This research introduces a single-supplier, a single-manufacturer, and multi-retailer-based three-echelon supply chain management under advertising and payment policies. Product delivery among supply chain players is made with the help of a transportation policy. The transportation policy is environment-friendly and helps retailers with their cost management. It is demonstrated that advertising positively influences sales through an advertisement driven market demand for the product. The model aims to reduce supply chain cost and maximize profit by considering a single-setup multiple-delivery policy, variable transportation cost, variable carbon emissions costs, and trade-credit policy. The objective function is optimized for cases: Case 1 and Case 2, based on the payment period. A classical optimization method is employed to obtain the solution of the model. A numerical example, sensitivity analysis, and graphical representations are given to illustrate the model. Results show that Case 2, where cycle time is greater than the payment period, is 45.36% more profitable than Case 1