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Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis (Paperback)
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Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis (Paperback)
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Master's Thesis from the year 2013 in the subject Engineering -
Industrial Engineering and Management, grade: Good, LMU Munich (Dr.
B R Ambedkar National Institute of Technology, Jalandhar), course:
Industrial Engg., language: English, abstract: Since the late
1940s, linear programming models have been used for many different
purposes. Airline companies apply these models to optimize their
use of planes and staff. NASA has been using them for many years to
optimize their use of limited resources. Oil companies use them to
optimize their refinery operations. Small and medium-sized
businesses use linear programming to solve a huge variety of
problems, often involving resource allocation. In my study, a
typical product-mix problem in a manufacturing system producing two
products (each product consists of two sub-assemblies) is solved
for its optimal solution through the use of the latest versions of
MATLAB having the command simlp, which is very much like linprog.
As analysts, we try to find a good enough solution for the decision
maker to make a final decision. Our attempt is to give the
mathematical description of the product-mix optimization problem
and bring the problem into a form ready to call MATLAB's simlp
command. The objective of this paper is to find the best product
mix that maximizes profit. The graph obtained using MATLAB
commands, give the shaded area enclosed by the constraints called
the feasible region, which is the set of points satisfying all the
constraints. To find the optimal solution we look at the lines of
equal profit to find the corner of the feasible region which yield
the highest profit. This corner can be found out at the farthest
line of equal profit which still touches the feasible region. The
most critical part is the sensitivity analysis using Excel Solver
and Parametric Analysis using computer software which allows us to
study the effect on optimal solution due to discrete and continuous
change in parameters of the LP model including
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