Linear Programming Operations Management: Summary
Linear programming operations management is a mathematical strategy that is employed for arranging scarce or limited resources effectively while performing various tasks. It is also a technique that organizations can use to achieve profit by reducing the costs of any price. There are two functions that are used in linear programming, namely, the objective and restraint functions (Woubante, 2017). The objective function refers to the variable attempted to develop solutions to problems in linear programming. The restraint function is implemented for generating constraints, while the objective function will use variables for solving them.
In order to improve processes at an organization, an application for linear programming operations management is used. For example, in the manufacturing industry, the application is used by companies in order to arrange the existing scarce resources efficiently and in accordance with the standards of the desired level of optimization. With the help of linear programming, manufacturers can manage their capabilities in terms of production volumes and determine the optimum workload that would yield maximum profitability and effectiveness. The method is used for determining the optimum level of service for a determined problem.
Since manufacturing requires the transformation of raw materials into specific products intended for maximizing their revenue. Therefore, each step of the manufacturing process must work as efficiently and effectively as possible. For instance, when dealing with raw materials, manufacturers pass them through different machines in an assembly line. A linear programming operations management application will allow the manufacturer to use a linear expression of the precise measurement of materials that should be used. In terms of constraints, it is imperative to consider the time that is spent on each piece of machinery.
When there are any bottlenecks in the performance of the equipment at manufacturing plants, the management is expected to eliminate them for avoiding any disruptions. The decision-making based on linear modeling can influence the number of products being manufactured for the purpose of maximizing profit on the basis of optimizing the use of raw materials as well as times needs for their processing.
Operations Management Linear Programming Application: Reaction
The article by Woubante (2017) is useful for understanding how to ensure that the resources used in the process of manufacturing yield the best outcomes possible. Linear programming applications facilitate positive decision-making on the part of manufacturers as well as enable them to optimize the product mix. Using the example of apparel firms, the author showed how the model could be used for improving the profitability of an organization by around 60%, which points to the effectiveness of linear programming as applied to the optimization of manufacturing. The article is valuable for shedding light on how the manufacturing industry should use its resources to achieve the best possible outcomes.
The application of linear programming results in significant improvements in resource use and subsequent profits, which are achieved with the help of quantitative measurements. Thus, it can be concluded that manufacturers can use the model for determining their optimum product mix. Specific recommendations that applied to the company explored in the study included the use of an operational search technique within the production time horizon in order to facilitate the improvement of organizational objectives. Overall, the use of linear programming applications in manufacturing offers wide opportunities for optimizing processes and using resources in a way that brings the best results in terms of profits.
References
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Cochran, J. L., Fry, M. J., & Ohlmann, J. W. (2016). Quantitative methods for business with CengageNOW (13th ed.). Boston, MA: Cengage Learning.
Woubante, G. (2017). The optimization problem of product mix and linear programming applications: Case study in the apparel industry. Open Science Journal, 2(2), 1-11.