Profit Optimization Using Linear Programming Model: A Case.
H. Crowder, E. Johnson, and M. Padberg, Solving Large-Scale Zero-One Linear Programming Problems, Operations Research 31 (1983), 803. R. Dakin, A Tree-Search Algorithm for Mixed Integer Programming Problems, The Computer Journal 8 (1964), 250.
This paper aims for profit optimization of an Ethiopian chemical company located in Adama (Ethiopia) using linear programming model. Particularly, our present study brings out clearly the necessity of using quantitative techniques for utilization in Ethiopian company; a factory situated within Adama about 90 kms. from Addis Ababa (Capital of Ethiopia).
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Linear programming solution examples Linear programming example 1997 UG exam. A company makes two products (X and Y) using two machines (A and B). Each unit of X that is produced requires 50 minutes processing time on machine A and 30 minutes processing time on machine B. Each unit of Y that is produced requires 24 minutes processing time on.
A suggested algorithm to solve fully rough integer linear programming (FRILP) problems is introduced in this paper in order to find rough value optimal solutions and decision rough integer variables, where all parameters and decision variables in the constraints and the objective function are rough intervals (RIs). In real-life situations, the parameters of linear programming problem model may.
Linear programming (LP, also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is a special case of mathematical programming (also known as mathematical optimization).
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In this paper, we make a further research on the coefficient-fuzzy linear programming. The constraint satisfactory function method and its deficiency are discussed. We introduced a new concept of the.
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with.
Arbel A. (1993),Exploring Interior-Point Linear Programming Algorithms and Software, MIT Press, Cambridge, MA. zbMATH Google Scholar.
Linear programming is a family of mathematical programming that is concerned with or useful for allocation of scarce or limited resources to several competing activities on the basis of given criterion of optimality. In statistics, linear programming (LP) is a special techniques employed in operation research for the purpose of.
In this paper, a joint optimal model for water allocation and water distribution network management is developed. In the first phase, a multi-objectives linear programming is used for the optimal allocation on multi-water resources for multi-users, in which cost and water conservation are regards as objectives. In the second phase, a non-linear.
In this research, Linear Programming has been used to optimize the use of resources. Resources can be anything that act as an input. They can be men, material, money or other assets that can be used by an organization or an individual in order to function effectively. There are laws available in linear programming that are very effective in optimizing the resources. They have been used in this.
