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Summary
Any business aims to optimize its processes in the most cost-efficient way possible. For organizations operating in the sphere of product manufacturing on a large scale, it is imperative to understand the way in which they can manage operations and increase efficiency and productivity (Anderson et al., 2016). Shortest route linear programming models are concerned with the application of the method in order to determine the fastest and the most beneficial solutions to a given problem. In the management of resources, the shortest route problems arise most frequently in the context of transportation.
For example, there is a problem for a delivery truck reaching multiple stores to distribute a product and doing so within the shortest time possible. Linear programming (LP) is thus used for obtaining the most beneficial and the least time-consuming solution. With the help pf the model, a life problem is formulated with the help of a mathematical model, which involves an objective function, and the linear inequalities subjected to constraints.
The research article by Ghazali, Abd Majid, and Shazwani (2012) explores the use of linear programming in regards to formulating optimal solutions to transportation problems. By using the case of a Malaysian trading company, the scholars explored the way in which an optimum plan can be developed to distribute goods across facilities. The shortest route problem, in this case, is concerned with minimizing the costs of transportation while also taking the least time possible.
Shortest route solutions are thus crucial for businesses the operations of which include transportation, with linear programming not only for solving problems but also helping organizations stay productive and competitive.
The researchers explored the use of linear programming in order to reduce shipping costs and meet the demand while staying within the maximum capacity levels. In order to develop a mathematical model, several information sections should be established. First, it is necessary to determine the number of supply points from products is shipped. Second, the set of demand destinations to which products are being shipped should be identified. Third, the scholar suggested determining variable costs.
Reaction
The authors mentioned that in logistics, each point of supply has specific supply capacity, while each destination has a particular demand to be fulfilled. Linear programming comes into play in such cases because of the need to facilitate the decision-making processes associated with finding suitable solutions. The study is useful for getting an understanding of how a mathematically developed model can be used in real life to solve problems related to transportation. As a result of the models integration into the management of transportation operations, it was possible to make calculations regarding the shortest route solutions.
By considering the capacity of facilities as well as their demands alongside with the distance between them, the researchers revealed a sufficient way of minimizing total costs of transportation and related processes. Overall, the researcher highlighted the use of linear programming when solving transportation problems. The LP model can become a useful tool available for both managers and engineers to ensure that the operations are being carried out at the lowest cost possible in order to maximize profits. The key takeaway of the article is the need to collect all preliminary data to guarantee the successful application of the tool when discovering the shortcuts to maximizing operations and efficiency.
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.
Ghazali, Z., Abd Majid, A., & Shazwani, M. (2012). Optimal solution of transportation problem using linear programming: A case of a Malaysian trading company. Journal of Applied Sciences, 12, 2430-2435.
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