Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights.

In today’s digital age, industrial methods are shifting away from humans and toward machines. We choose automated systems for various jobs related to production systems, such as screening, manufacturing. A smart manufacturing system is one in which machines take the place of humans. Under the influence of inflation, this study proposes a smart production-inventory model with partial backlogging, and an imperfect manufacturing process where the deterioration rate is constant. Every production system, in reality, has a random defect rate. A screening procedure is required due to the manufacture of some defective items, which is carried out by machine, i.e., by an automated system. Carbon is released during the manufacturing process due to actions such as holding deterioration. As a result, carbon emissions are taken into account in the current study. The goal of this study is to reduce total inventory costs as much as possible. To demonstrate the proposed model’s practical application, many numerical examples and sensitivity assessments with graphs are provided.

The present paper investigated the economic order quantity inventory model for a retailer under two-levels of trade credit to reflect the supply chain management (SCM). Here, it is assumed that the selling items are perishable such as fruits, fresh fishes, gasoline, photographic films, etc. It is assumed that potential worth of items can be increased by using preservation technology and the retailer's trade credit period (M) offered by the supplier is longer than the customer's trade credit period (N) offered by the retailer. It also assumed that the demand of the customer depends on the selling price of items. Theorems are developed to determine retailer's optimal ordering policies and numerical examples are given to illustrate these theorems. It also observed that Goyal (1985), Shah (1993), Chung (1998) and Huang (2003) are the particular case of our proposed model. In addition, some managerial insights from the numerical examples are also concluded.

Multi-item inventory model for deteriorating items with stock dependent demand under two-warehouse system is developed in fuzzy environment (purchase cost, investment amount and storehouse capacity are imprecise ) under inflation and time value of money. For display and storage, the retailers hire one warehouse of finite capacity at market place, treated as their own warehouse (OW), and another warehouse of imprecise capacity which may be required at some place distant from the market, treated as a rented warehouse (RW). Joint replenishment and simultaneous transfer of items from one warehouse to another is proposed using basic period (BP) policy. As some parameters are fuzzy in nature, objective (average profit) functions as well as some constraints are imprecise in nature, too. The model is formulated so to optimize the possibility/necessity measure of the fuzzy goal of the objective functions, and the constraints satisfy some pre-defined necessity. A genetic algorithm (GA) is used to solve the model, which is illustrated on a numerical example.