We study a set of scheduling problems on a uniform machine setting. We focus on the case of equal processing time jobs with the additional feature of job rejection. Jobs can either be processed on a predefined set of machines or rejected. Rejected jobs incur a rejection penalty and have no effect on the scheduling criterion under consideration. A solution to our problems consists of partitioning the jobs into two subsets, A\documentclass[12pt]{minimal}
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\begin{document}$$A$$\end{document} and A¯\documentclass[12pt]{minimal}
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\begin{document}$$\overline{A}$$\end{document}, which are the set of accepted and the set of rejected jobs, respectively. In addition, jobs in set A\documentclass[12pt]{minimal}
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\begin{document}$$A$$\end{document} have to be scheduled on the m\documentclass[12pt]{minimal}
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\begin{document}$$m$$\end{document} machines. We evaluate the quality of a solution by two criteria. The first, F1\documentclass[12pt]{minimal}
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\begin{document}$$F_{1}$$\end{document}, can be any regular scheduling criterion, while the latter, F2\documentclass[12pt]{minimal}
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\begin{document}$$F_{2}$$\end{document}, is the total rejection cost. We consider two possible types of regular scheduling criteria; the former is a maximization criterion, while the latter is a summation criterion. For each criterion type we consider four different problem variations. We prove that all four variations are solvable in polynomial time for any\documentclass[12pt]{minimal}
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\begin{document}$$any$$\end{document} maximization type of a regular scheduling criterion. When the scheduling criterion is of summation type, we show that only one of the four problem variations is solvable in polynomial time. We provide a pseudo-polynomial time algorithms to solve interesting variants of the NP\documentclass[12pt]{minimal}
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\begin{document}$$\mathcal {NP}$$\end{document}-hard problems, as well as a polynomial time algorithm that solves various other special cases.
