In the lawn mower production problem in Example 8.4, the model changeover cost dominates...

In the lawn mower production problem in Example 8.4, the model changeover cost dominates in the optimal objective value. Is this because we assumed such a large unit penalty cost, 200, for each model changeover? Explore this question by changing this unit penalty cost to lower values such as 100 and 50 (or even smaller). What happens to the optimal solution?

(Reference Example 8.4)

EasyRide, a lawn mower manufacturer, needs to set its weekly production schedule for the next four weeks. The company produces seven models of lawn mowers. At the beginning of each month, the company has reasonably accurate forecasts for the demand of each model for the month. It also has forecasts for the portion of this demand from customers who will drive to the plant to pick up their lawn mowers. The company has four competing objectives regarding its production schedule.

¦ Avoid costly model changeovers during each week as much as possible.

¦ Come as close as possible to producing the mowers demanded by customers during week 1 (assuming the “pickup” customers, those who drive to the plant to pick up their mowers, typically arrive during week 1).

¦ Keep weekly production hours as constant as possible across weeks at each of the three machining centers that the models go through.

¦ Come as close as possible to producing as many mowers of each model as its monthly forecasts require.

Objective To use Evolutionary Solver to find a production schedule that achieves the company’s goals as fully as possible.

WHERE DO THE NUMBERS COME FROM?

As in other production scheduling models we have discussed, the most crucial inputs are the demand forecasts. The company presumably has a method for forecasting demands, probably based on historical data and orders already on the books.