Single-machine scheduling with fixed energy recharging times to minimize the number of late jobs and the number of just-in-time jobs: A parameterized complexity analysis

IF 6 2区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE European Journal of Operational Research Pub Date : 2025-07-01 Epub Date: 2025-02-03 DOI:10.1016/j.ejor.2025.01.007
Renjie Yu, Daniel Oron
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Abstract

We study single-machine scheduling problems where processing each job requires both processing time and rechargeable energy. Subject to a predefined energy capacity, energy can be recharged after each job during a fixed recharging period. Our focus is on two due date-related scheduling criteria: minimizing the number of late jobs and maximizing the weighted number of jobs completed exactly at their due dates. This study aims to analyze the parameterized tractability of the two problems and develop fixed-parameter algorithms with respect to three natural parameters: the number of different due dates vd, the number of different processing times vp, and the number of different energy consumptions ve. Following the proofs of NP-hardness across several contexts, we demonstrate that both problems remain intractable when parameterized by vd and vp. To complement our results, we show that both problems become fixed-parameter tractable (FPT) when parameterized by ve and vd, and are solvable in polynomial time when both ve and vp are constant.
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具有固定能量充电时间的单机调度以最小化延迟作业数量和准时作业数量:参数化复杂性分析
我们研究了单机调度问题,其中每个作业都需要处理时间和可充电能量。根据预定义的能量容量,可以在固定的充电周期内,在每个作业后进行能量充电。我们的重点是两个与截止日期相关的调度标准:最小化延迟作业的数量和最大化恰好在截止日期完成的加权作业数量。本研究旨在分析这两个问题的参数化可跟踪性,并针对三个自然参数:不同到期日数vd、不同处理时间数vp和不同能耗数ve,开发固定参数算法。在几种情况下证明np -硬度之后,我们证明当用vd和vp参数化时,这两个问题仍然难以解决。为了补充我们的结果,我们证明当用ve和vd参数化时,这两个问题都是固定参数可处理的(FPT),当ve和vp都是常数时,这两个问题在多项式时间内可解。
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来源期刊
European Journal of Operational Research
European Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
11.90
自引率
9.40%
发文量
786
审稿时长
8.2 months
期刊介绍: The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.
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