Application of Linear Programming in Business Decision-Making

Abstract Linear Programming (LP) is an important quantitative technique used to support effective decision-making in business and management. It provides a systematic mathematical approach for allocating limited resources among competing activities while maximizing profit or minimizing costs. The present study examines the application of linear programming in business decision-making, with particular emphasis on production planning, resource allocation, product-mix decisions, transportation, inventory management, and cost optimization. The study explains how linear programming models can assist managers in identifying optimal solutions subject to various business constraints, including limited labour, raw materials, production capacity, capital, and market demand. The research is based primarily on secondary data and reviews relevant literature concerning the application of quantitative techniques and optimization models in business. The study finds that linear programming can improve resource utilization, reduce unnecessary costs, support production planning, and provide a rational basis for managerial decisions. However, the effectiveness of an LP model depends on the accuracy of assumptions, quality of data, and appropriate formulation of the objective function and constraints. The study concludes that linear programming remains a valuable decision-support technique and can be integrated with modern data analytics and computational tools to address increasingly complex business problems.