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Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis - In MATLAB and Excel Solver (Paperback)
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Strategic Allocation of Resources Using Linear Programming Model with Parametric Analysis - In MATLAB and Excel Solver (Paperback)
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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 study 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 to identify bottlenecks. We have examined other
options like product outsourcing, one-time cost, cross training of
one operator, manufacturing of hypothetical third product on
under-utilized machines and optimal sequencing of jobs on machine
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