{"title":"双目标 JIT 调度问题的帕累托最优前沿生成,目标之间存在片断线性权衡","authors":"Sona Babu, B.S. Girish","doi":"10.1016/j.orp.2024.100299","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted earliness and tardiness (TWET) and total flowtime (TFT) objectives in a single-machine scheduling problem (SMSP) with distinct job due dates allowing inserted idle times in the schedules. An optimal timing algorithm (OTA) is presented to generate the trade-off curve between TWET and TFT for a given sequence of jobs. The proposed method of Pareto front generation generates a Pareto-optimal front constituted of both line segments and points. Further, we employ a simple local search method to generate sequences of jobs and their respective trade-off curves, which are trimmed and merged to generate the Pareto-optimal front using the proposed method. Computational results obtained using problem instances of different sizes reveal the efficiency of the proposed OTA and the Pareto front generation method over the state-of-the-art methodologies adopted from the literature.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716024000034/pdfft?md5=5b11514fe1b1cb59cc8b7fbe08ee9aed&pid=1-s2.0-S2214716024000034-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Pareto-optimal front generation for the bi-objective JIT scheduling problems with a piecewise linear trade-off between objectives\",\"authors\":\"Sona Babu, B.S. Girish\",\"doi\":\"10.1016/j.orp.2024.100299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted earliness and tardiness (TWET) and total flowtime (TFT) objectives in a single-machine scheduling problem (SMSP) with distinct job due dates allowing inserted idle times in the schedules. An optimal timing algorithm (OTA) is presented to generate the trade-off curve between TWET and TFT for a given sequence of jobs. The proposed method of Pareto front generation generates a Pareto-optimal front constituted of both line segments and points. Further, we employ a simple local search method to generate sequences of jobs and their respective trade-off curves, which are trimmed and merged to generate the Pareto-optimal front using the proposed method. Computational results obtained using problem instances of different sizes reveal the efficiency of the proposed OTA and the Pareto front generation method over the state-of-the-art methodologies adopted from the literature.</p></div>\",\"PeriodicalId\":38055,\"journal\":{\"name\":\"Operations Research Perspectives\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2214716024000034/pdfft?md5=5b11514fe1b1cb59cc8b7fbe08ee9aed&pid=1-s2.0-S2214716024000034-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Perspectives\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214716024000034\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Perspectives","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214716024000034","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了一种新方法,即从双目标及时调度(JIT)问题中通常会遇到的一组片断线性权衡曲线中生成帕累托前沿。我们考虑了在单机调度问题(SMSP)中同时最小化总加权提前和延迟(TWET)目标和总流动时间(TFT)目标的问题,该问题具有不同的作业到期日,允许在调度中插入空闲时间。本文提出了一种最佳时间算法 (OTA),用于生成给定作业序列中 TWET 和 TFT 之间的权衡曲线。所提出的帕累托前沿生成方法可生成由线段和点构成的帕累托最优前沿。此外,我们还采用了一种简单的局部搜索方法来生成工作序列及其各自的权衡曲线,并利用所提出的方法对这些曲线进行修剪和合并,从而生成帕累托最优前沿。利用不同大小的问题实例获得的计算结果显示,与文献中采用的最先进方法相比,建议的 OTA 和帕累托前沿生成方法非常高效。
Pareto-optimal front generation for the bi-objective JIT scheduling problems with a piecewise linear trade-off between objectives
This paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted earliness and tardiness (TWET) and total flowtime (TFT) objectives in a single-machine scheduling problem (SMSP) with distinct job due dates allowing inserted idle times in the schedules. An optimal timing algorithm (OTA) is presented to generate the trade-off curve between TWET and TFT for a given sequence of jobs. The proposed method of Pareto front generation generates a Pareto-optimal front constituted of both line segments and points. Further, we employ a simple local search method to generate sequences of jobs and their respective trade-off curves, which are trimmed and merged to generate the Pareto-optimal front using the proposed method. Computational results obtained using problem instances of different sizes reveal the efficiency of the proposed OTA and the Pareto front generation method over the state-of-the-art methodologies adopted from the literature.