Repeat Problem 20, but now assume there is a setup time for changing from any job to another job, and this setup time can depend on the jobs. For example, the setup time when changing from job 2 to...

Repeat Problem 20, but now assume there is a setup time for changing from any job to another job, and this setup time can depend on the jobs. For example, the setup time when changing from job 2 to job 4 can be different from the setup time when changing from job 3 to job 4. The data from Problem 20, plus the setup times, are listed in the file P08_22.xlsx. Use Evolutionary Solver to find an optimal sequence of jobs.

An important problem in operations management is the job sequencing problem. Actually, there are many versions of this problem, but they all basically attempt to find the proper sequencing of jobs on a machine. Here is one version of the problem. There are 10 jobs to perform on a single machine. Each job has a given batch size (items to produce), and each item in the batch takes a certain time to perform. Also, each job (the whole batch) has a given due date. These data are listed in the file P08_20.xlsx. The “lateness” of any job is 0 if the job is finished on or before its due date, but it is the finish time minus the due date otherwise. The objective is to sequence the jobs to minimize the total lateness. Use Evolutionary Solver to find an optimal sequence of jobs.