A Study on Application of Linear Programming on Product Mix for Profit Maximization and Cost Optimization

Abstract

Objectives: This research aims to sneak into the retailer's perception about that customer segment and plan a product mix accordingly. The focus is on small players in small towns not having deep pockets to synergize the product mix decisions effectively. Methods: The data used in this research paper is from Hatchers, a medium-sized enterprise with zero budget for software for product mix decisions. The data was collected through face-to-face interviews with ten representatives and five supervisors in compliance with the existing documents and existing datasheet obtained from the production department, which was slightly updated to make the final output. The data was for one season, i.e., April to March. The data was analyzed to study pre-Linear Programming and post-Linear Programing profits. Findings: This examination distinguishes the current asset usage level and the benefit of every period of one of the apparel producing organizations, utilizing a linear programming procedure. Actual consumption of resources (product wise) was calculated to evaluate profit post applying Linear Programing to see the wastage and cost. There was a 54% increase post LP compared to the product-wise resource utilization. Similarly, the profit using Linear programming was more than double as wastage and costing were minimum, and revenue was high. Novelty: The article focused on the simple basic principle of linear programming for identifying product mix using Excel(Solver). LINGO. The software solutions become costlier for small firms, whereas Excel is more accessible and cost-efficient. There is a gap in existing literature as previous research has not focused on this aspect for small business houses where adapting software solutions is challenging.

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