Approximation algorithms for identical parallel machine scheduling with assignment costs

Abstract

We study non-preemptive scheduling on identical parallel machines in which assigning job $j$ to machine $M_i$ incurs the cost $c_{ij}=a_iw_j+b_j$. The processing times $p_j$ and the cost weights $w_j$ are independent, and the number of machines is part of the input. For every fixed $\varepsilon\in(0,1]$ and every deadline $T$ for which a schedule with makespan at most $T$ exists, we give a polynomial-time algorithm that computes a schedule with makespan at most $(1+\varepsilon)T$ whose total assignment cost does not exceed the minimum under the deadline $T$. Using this algorithm as a subroutine, we obtain a polynomial-time approximation scheme for minimizing the makespan under a total cost budget whose schedules always satisfy the budget; this answers an open question for costs $c_{ij}=l_ic_j$ with $c_j$ independent of $p_j$. For the lexicographic problem, in which the total assignment cost is minimized among all schedules of minimum makespan, we obtain in polynomial time a schedule with makespan at most $1+\varepsilon$ times the minimum and total assignment cost at most that of a lexicographically optimal schedule; this improves the makespan guarantees of earlier algorithms for additive and multiplicative costs. For costs $c_{ij}=s_i+a_iw_j$, where $s_i$ is charged for each job processed on $M_i$, the same guarantees are obtained in quasi-polynomial time.