Optimizing Simultaneous Decisions | Assignment

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Optimizing Simultaneous Decisions
Student Name
Institution Name
Date

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Part A
Decision making scenario
Linear programming can be applied in a business set up to obtain the best way of
maximizing profits or minimizing the operational costs. In this case the decision-making
scenario involves production planning. To optimize production where various goods are to be
manufactured, the firm can apply linear programming to decide on the optimal quantity of each
product that ought to be produced taking into account the various constraints (Akpan & Iwok,
2016). The business scenario in question is making furniture (chairs, beds, tables). The decision
to be made is how many of each item should be produced by the firm in a given month to
maximize the profits.
Best initial gauze
In this business scenario the objective is to maximize the total profits from the furniture
production. The decision variables are the number of chairs, tables and beds that are to be
produced in a given month. Due to policy, resource and market limitation the decision will be
faced by a number of constraints some of them include:
Units produced should not be below the demanded units.
Production cost should be in line with the allocated capital.
Production hours should be less or equal to the available hours.
Tactical decision making
One tactical decision that will be dine after obtaining the optimal solution is sensitivity
analysis. This will be carried out to estimate how changes in the various aspects of production
will influence the total profit obtained.
Part B
Screenshot of best result

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Approach taken
The first step taken was to set the initial decision variables to 0 and solve the model using
GRG nonlinear, then Simplex LP and finally Evolutionary method. I did repeat the steps but this
time round set the initial decision variables to 1. Afterwards I tried experimenting with the
options by using the multi-start option for the GRG nonlinear method. All the trials did give the
screenshot above as the best possible value that achieves the objective.
Part one: Creation of linear optimization model
1. Objective of the problem
The objective of this problem is to accept bids that will ensure supply of the necessary
packaging materials needed for the products at the minimum cost. The problem objective
is thus to minimize the total cost associated with suppl tog packaging materials.
2. Decision variables
The decision variables are the units of products to accepts under each bid that has been
submitted by the supplies.
3. Constraints
The decision is limited by the following constraints:
The total units of products accepted from the bids should equal or exceed the minimum
packaging units required for each product.