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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.

Fixed Order Scheduling with Deadlines

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 -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 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 -approximation.

Paper Structure

This paper contains 12 sections, 14 theorems, 39 equations, 6 figures.

Key Result

lemma 1

Next-fit has an unbounded approximation ratio for the instance $\mathcal{I}_n$.

Figures (6)

  • Figure 1: The optimal schedule and the schedule by NF for $\mathcal{I}_n$ where $n\geq 5$.
  • Figure 2: Exchanging the jobs between two machines of $\tau^*$ when $s = s^*$.
  • Figure 3: Exchanging the jobs between two machines of $\tau^*$ when $s > s^*$.
  • Figure 4: An example with the approximation ratio of $(2k+1)/(k+1).$
  • Figure 5: An example of the placement of jobs $e^*_i$ in the OPT and FF schedules.
  • ...and 1 more figures

Theorems & Definitions (20)

  • lemma 1
  • theorem 1
  • Claim 1
  • Claim 2
  • lemma 2
  • theorem 2
  • Claim 3
  • Claim 4
  • theorem 3
  • theorem 4
  • ...and 10 more