Fixed Order Scheduling with Deadlines
Andre Berger, Arman Rouhani, Marc Schröder
TL;DR
This paper investigates scheduling on identical parallel machines with a fixed global processing order on each machine, under common release times and deadlines, aiming to minimize the number of machines. It analyzes two greedy strategies, establishing that Next-Fit can perform arbitrarily badly, while First-Fit provides optimality for unit processing times and a 2-approximation in several natural order-structures, with a general $O(\log n)$-approximation for arbitrary orders. The results delineate when simple greedy schedules suffice and provide a framework—via slacks, deadlines, and a set-cover reduction—for approximating fixed-order SRDM variants. The findings have practical relevance for energy-aware scheduling and fixed-priority systems and point to future work on tighter bounds and additional algorithms.
Abstract
This paper studies a scheduling problem in a parallel machine setting, where each machine must adhere to a predetermined fixed order for processing the jobs. Given $n$ jobs, each with processing times and deadlines, we aim to minimize the number of machines while ensuring deadlines are met and the fixed order is maintained. We show that the first-fit algorithm solves the problem optimally with unit processing times and is a 2-approximation in the following four cases: (1) the order aligns with non-increasing slacks, (2) the order aligns with non-decreasing slacks, (3) the order aligns with non-increasing deadlines, and (4) the optimal solution uses at most 3 machines. For the general problem we provide an $O(\log n)$-approximation.
