Scheduling with competing agents, total late work and job rejection

We study a single-machine scheduling problem with two competing agents. The objective function of one agent is minimizing total late work, whereas the maximum cost of the jobs of the second agent cannot exceed a given upper bound. We introduce and test a pseudo-polynomial dynamic programming algorithm for this NP-hard problem. Our tests indicate that the algorithm can handle large-size instances (containing hundreds of jobs) fairly quickly. We then extend the setting to that of job rejection, where the scheduler may decide to process only a subset of the jobs. The dynamic programming algorithm is modified accordingly, and our numerical tests verify that medium-size instances (containing less than 100 jobs) are solved in reasonable time.