In a controllable scheduling environment, the processing time of a job can be shortened by allocating extra resource at a cost, or the job can be declined for processing by paying a penalty. We investigate the single machine controllable scheduling to minimize the sum of the total resource consumption cost, the total job rejection cost, and the makespan of the accepted jobs, where the makespan is upper bounded and the job processing time is a decreasing linear function in the amount of allocated resource. We first show that the studied problem is polynomial solvable if the makespan is unbounded, but otherwise is NP-hard, and characterize important structural properties for the optimal solution; we then take advantage of the structural properties to design several algorithms for the problem, including a pseudo-polynomial time dynamic programming exact algorithm, an O ( n 2 )-time n -approximation algorithm where n is the number of jobs, and building on top of the dynamic programming exact algorithm, the n -approximation algorithm and the bound improvement procedure, two fully polynomial time approximation schemes.

We consider the single machine scheduling problem with job-dependent machine deterioration. In the problem, we are given a single machine with an initial non-negative maintenance level, and a set of jobs each with a non-preemptive processing time and a machine deterioration. Such a machine deterioration quantifies the decrement in the machine maintenance level after processing the job. To avoid machine breakdown, one should guarantee a non-negative maintenance level at any time point; and whenever necessary, a maintenance activity must be allocated for restoring the machine maintenance level. The goal of the problem is to schedule the jobs and the maintenance activities such that the total completion time of jobs is minimized. There are two variants of maintenance activities: in the partial maintenance case each activity can be allocated to increase the machine maintenance level to any level not exceeding the maximum; in the full maintenance case every activity must be allocated to increase the machine maintenance level to the maximum. In a recent work, the problem in the full maintenance case has been proven NP-hard; several special cases of the problem in the partial maintenance case were shown solvable in polynomial time, but the complexity of the general problem is left open. In this paper we first prove that the problem in the partial maintenance case is NP-hard, thus settling the open problem; we then design a 2-approximation algorithm.