On the optimality of approximation schemes for the classical scheduling problem (1310.0398v1)

Abstract: We consider the classical scheduling problem on parallel identical machines to minimize the makespan, and achieve the following results under the Exponential Time Hypothesis (ETH) 1. The scheduling problem on a constant number $m$ of identical machines, which is denoted as $Pm||C_{max}$, is known to admit a fully polynomial time approximation scheme (FPTAS) of running time $O(n) + (1/\epsilon)^{O(m)}$ (indeed, the algorithm works for an even more general problem where machines are unrelated). We prove this algorithm is essentially the best possible in the sense that a $(1/\epsilon)^{O(m^{1-\delta})}+n^{O(1)}$ time FPTAS for any $\delta>0$ implies that ETH fails. 2. The scheduling problem on an arbitrary number of identical machines, which is denoted as $P||C_{max}$, is known to admit a polynomial time approximation scheme (PTAS) of running time $2^{O(1/\epsilon^2\log^3(1/\epsilon))}+n^{O(1)}$. We prove this algorithm is nearly optimal in the sense that a $2^{O((1/\epsilon)^{1-\delta})}+n^{O(1)}$ time PTAS for any $\delta>0$ implies that ETH fails, leaving a small room for improvement. To obtain these results we will provide two new reductions from 3SAT, one for $Pm||C_{max}$ and another for $P||C_{max}$. Indeed, the new reductions explore the structure of scheduling problems and can also lead to other interesting results. For example, using the framework of our reduction for $P||C_{max}$, Chen et al. (arXiv:1306.3727) is able to prove the APX-hardness of the scheduling problem in which the matrix of job processing times $P=(p_{ij})_{m\times n}$ is of rank 3, solving the open problem mentioned by Bhaskara et al. (SODA 2013).