A $(2+\varepsilon)$-approximation algorithm for preemptive weighted flow time on a single machine
Lars Rohwedder, Andreas Wiese

TL;DR
This paper presents a new polynomial-time algorithm that approximates the minimum weighted flow time on a single machine within a factor of 2+epsilon, improving previous bounds and avoiding LP-rounding.
Contribution
It introduces a novel reduction to a geometric problem and a dynamic programming approach, achieving a 2+epsilon approximation without LP-rounding.
Findings
Achieves a 2+epsilon approximation ratio.
Reduces the problem to a geometric problem with minimal loss.
Avoids LP-rounding by leveraging structural properties.
Abstract
Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. The input consists of a set of jobs, characterized by their processing times, release times, and weights and we want to compute a (possibly preemptive) schedule for them. The objective is to minimize the sum of the weighted flow times of the jobs, where the flow time of a job is the time between its release date and its completion time. It had been a long-standing open problem to find a polynomial time -approximation algorithm for this setting. In a recent break-through result, Batra, Garg, and Kumar (FOCS 2018) found such an algorithm if the input data are polynomially bounded integers, and Feige, Kulkarni, and Li (SODA 2019) presented a black-box reduction to this setting. The resulting approximation ratio is a…
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Taxonomy
TopicsScheduling and Optimization Algorithms · Optimization and Search Problems · Optimization and Packing Problems
