Aggregate Planning Using Linear Programming

The first step in constructing an aggregate planning model is to identily the set of decision variables whose values are to be determined as part of the aggregate plan. For Red Tomato, the following decision variables are defined for the aggregate planning model  

The next step in constructing an aggregate planning model is to define the objective function. 

Denote the demand in Period t by Dp The values of D, are as specified by the demand forecast in Table 8-2. The objective function is to minimize the total cost (equivalent to maximizing total profit as all demand is to be satisfied) incurred during the planning horizon. The cost incurred has the following components  

Regular-time labor cost. Recall that workers are paid a regular-time wage of 640 (S4/hour X 8 hours/day X 20 days/month) per month. Because is the number of workers in Period t, the regular-time labor cost over the planning horizon is given by 

Overtime labor cost. As overtime labor cost is 6 per hour (see Table 8-3) and Of represents the number of overtime hours worked in Period t, the overtime cost over the planning horizon is 

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Use Linear Programming to perform aggregate planning to decide the production and material requirements et al. Convert raw material into products according to production plan. 

In the next section, we explain how to implement the linear programming methodology for aggregate planning using Microsoft Excel. 

Next we discuss how to generate the aggregate plan for Red Tomato in Table 8-4 using Excel. We first do so by building a simple spreadsheet that allows vv/raM/analysis and then build a more sophisticated model that allows optimization using linear programming. 

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