Near-Linear Approximation Algorithms for Scheduling Problems with Batch Setup Times
Max A. Deppert, Klaus Jansen

TL;DR
This paper introduces near-linear approximation algorithms for scheduling jobs with batch setup times on identical machines, achieving improved approximation ratios and running times across various job preemption and parallelization models.
Contribution
It presents the first algorithms improving the approximation ratio from 2 to 3/2 for preemptive scheduling with setup times, with efficient running times for different problem variants.
Findings
Achieved a 3/2 approximation ratio for preemptive scheduling with setup times.
Developed near-linear time algorithms with various approximation ratios.
Progressed towards a PTAS for preemptive scheduling with setup times.
Abstract
We investigate the scheduling of jobs divided into classes on identical parallel machines. For every class there is a setup time which is required whenever a machine switches from the processing of one class to another class. The objective is to find a schedule that minimizes the makespan. We give near-linear approximation algorithms for the following problem variants: the non-preemptive context where jobs may not be preempted, the preemptive context where jobs may be preempted but not parallelized, as well as the splittable context where jobs may be preempted and parallelized. We present the first algorithm improving the previously best approximation ratio of to a better ratio of in the preemptive case. In more detail, for all three flavors we present an approximation ratio with running time , ratio in time…
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