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.

在当前的社会经济形势下，由于各种不可避免的原因，商业部门对必需品的日常需求一直在变化。因此，为盈利业务选择正确的方法变得相当棘手。本研究介绍了基于恒定和模糊需求的不同业务策略。在该模型中考虑了两种类型的约束来避免延期交货成本。然而，本研究将服务水平约束与恒定和模糊需求相结合，比较总成本，最终建立最佳策略。此外，这种模式投资少，提高了产品质量，降低了供应商的设置成本。根据运输产品的数量，该模型遵循运输折扣政策，以最低交货率轻松交付产品。采用 Kuhn-Tucker 优化技术，并使用 Hessian 矩阵从数值上验证全局最优性。通过比较研究、数值示例、敏感性分析、图形表示和管理见解讨论了该模型的稳健性。最后，讨论了一些总结性评论以及未来的扩展。