Insight into Linear Programming - Understand It with Different Scenari

Linear- the mirror for Rational A linear programming methodology has much in common with the rational decision making model and hence, it can be observed that it is actually a step by step replica of it. The rational decision making model had its foundation laid over a framework of multi-step process model which identifies, analyzes and decides. Similarly, linear programming defines, evaluates and gives a decision thereafter. The alternatives are weighed up, and sorted for best possible fit. The decision is based over optimization by either maximizing the profits or minimizing the costs. Rational decision making sets up the problem domain similarly to linear programming into which real world problems are mapped mathematically. Then alternatives are identified, chosen and implemented similar to linear programming in which the best possible alternative is executed and decided for evaluation of the value. Real wold scenario In real life projects linear programming is put into practice for optimization problems which have constraints or conditions which are not subject to dynamism and have a stable trend. For maximizing the production benefits and minimizing the raw material cost, these techniques are efficiently put into practice. Starting from its development for military purposes, it is widespread into the industry now for use in manufacturing, trading, health services, agriculture, planning and scheduling, research and development etc. They are used for resource allocation problems for best possible optimization of limited resources such as money, manforce, energy, technology, jobs, profits etc. It can be used for product mix problems,investment planning, marketing scheduling, and blending of strategy formulations. The inherent approach Linear programming is one of the started with mathematical fields have its existence and practices into industries and trade nowadays. This is a decision making procedure or a verification mechanism to ascertain reliability and accuracy of decisions taken with other models or approaches. It enhances and refines the quality of decision making by unifying the results from various domains of functioning and design. It is much flexible in its approach and is successful in analyzing multi-dimensional problems. By continuous evaluation and analysis, linear programming practices provides a database for judicious allocation of scarce resources. It is a definite edge over traditional and conventional solving methods. Linear programming can give a detailed account of limitations of the projects to provide optimization to the goals. For a quality decision making using linear programming process, it focuses over the midway areas or the potential bottlenecks occurring in constraint or problem rec ognition or formulation. The cons of linear programming The real life problems which may include numerous variables of concern and multiple dimensions of constraints and conditions cannot be well handled in the domain of linear programming. Every problem cannot be mapped into mathematical terms and when it comes to real life with diverse situations it is next to impossible or just really time consuming. There may be several areas of constraint implementation and all of them cannot be well covered up like social, financial, or institutional changes. The greatest challenge assumption of linear nature of problems. In the time of changes linear practices can only solve a certain type of optimization problems and hence cannot be put into action in real domain. Linear programming generally takes fractional values in account but products normally take up integer values. Finally, mapping the problems of the real world to set of some linear equations is difficult.