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To ensure all products as perfect, inspection is essential, even though it is not possible to inspect all products after producing them like some special type products as plastic joint for the water pipe. In this direction, this paper develops an inventory model with lot inspection policy. With the help of lot inspection, all products need not to be verified still the retailer can decide the quality of products during inspection. If retailer founds products as imperfect quality, the products are sent back to supplier. As it is lot inspection, mis-clarification errors (Type-I error and Type-II error) are introduced to model the problem. Two possible cases are discussed for sending back products as defective lots are immediately withdrawn from the system and send back to supplier with retailer's payment and for second case, retailer sends defective products during receiving next lot from supplier with supplier's investment, like in food industry or in hygiene product industry. The model is solved analytically and results indicate that optimal order size and sample size are intrinsically linked and maximize the total profit. Numerical examples, graphical representations, and sensitivity analysis are given to illustrate the model. The results suggest that sending defective products maintaining the first case is the more profitable than the second case.

Recently, carbon emission becomes a major issue during transportation of products from one player to another player. Due to the increasing number of single-setup-multi-delivery (SSMD) policies by several industries, fixed and variable transportation cost and carbon emission cost are considered. The aim of the model is to reduce the total cost of supply chain for controlling the lead time and to diminish setup cost by a discrete investment. A premium cost is introduced and Stackelberg game policy is employed to obtain the analytical solution. Some numerical examples are given to validate the model. Sensitivity analysis and managerial insights are given to show the applicability of the model. Finally, the outcomes show that the model minimizes the optimum cost at the optimal values of the decision variables. It is found that the total cost is minimized when the multi-buyer is leader and vendor is follower.

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