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Asia-Pacific Journal of Operational Research最新文献

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Optimality Conditions and Gradient Descent Newton Pursuit for 0/1-Loss and Sparsity Constrained Optimization 0/1损失和稀疏约束优化的最优性条件和梯度下降牛顿寻优
4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-10-27 DOI: 10.1142/s0217595923500355
Dongrui Wang, Hui Zhang, Penghe Zhang, Naihua Xiu
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引用次数: 0
Implications of refurbishing authorization strategy and distribution channel choice in a closed-loop supply chain 闭环供应链中翻新授权策略与分销渠道选择的意义
4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-10-20 DOI: 10.1142/s0217595923500331
Xujin Pu, Mingzhuo Dai, Wen Zhang
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引用次数: 0
On proper separation theorems by means of the quasi-relative interior with applications 拟相对内蕴的适当分离定理及其应用
4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-10-20 DOI: 10.1142/s021759592350032x
Tijani Amahroq, Hassan Khatite, Abdessamad Oussarhan
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引用次数: 0
Competitive influence maximization with uncertain competitor sources and the bandwagon effect in social networks 竞争对手来源不确定的竞争影响力最大化与社会网络中的从众效应
4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-10-20 DOI: 10.1142/s0217595923500343
Tao Sun, Suning Gong, Guo-Qiang Fan, Gongjie Xu
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引用次数: 0
Improved accelerated gradient algorithms with line search for smooth convex optimization problem 改进的直线搜索加速梯度算法求解光滑凸优化问题
4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-10-13 DOI: 10.1142/s0217595923500306
Ting Li, Yongzhong Song, Xingju Cai
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引用次数: 0
An inexact semismooth Newton-Based Augmented Lagrangian Algorithm for Multi-Task Lasso Problems 求解多任务Lasso问题的一种不精确的基于牛顿的增广拉格朗日算法
IF 1.4 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-09-05 DOI: 10.1142/s0217595923500276
Lanyu Lin, Yongjun Liu
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引用次数: 0
Preface — Special Issue: Machine Learning and Optimization II 前言——特刊:机器学习与优化II
IF 1.4 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-08-29 DOI: 10.1142/s0217595923020037
Yong Chen, Dingzhu Du, Chenchen Wu
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引用次数: 0
Controllable processing time scheduling with total weighted completion time objective and deteriorating jobs 具有总加权完成时间目标和恶化作业的可控加工时间调度
IF 1.4 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-08-11 DOI: 10.1142/s0217595923500264
Ji-Bo Wang, Yi-Chun Wang, Congying Wan, Dan-Yang Lv, Lei Zhang
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引用次数: 0
Preface: Special Issue of “Machine Learning and Optimization of MLO 2022” 前言:《MLO 2022机器学习与优化》特刊
IF 1.4 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-07-10 DOI: 10.1142/s0217595923020025
Yong Chen, Dingzhu Du, Chenchen Wu
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引用次数: 0
Minimizing Total Weighted Late Work in a Proportionate Flow Shop with Job Rejection 在有作业拒绝的比例流程车间中最小化总加权延迟工作
IF 1.4 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Pub Date : 2023-07-10 DOI: 10.1142/s0217595923500239
Ren-Xia Chen, Shisheng Li, Q. Feng
In this paper, we investigate a scheduling problem with optional job rejection in a proportionate flow shop setting, where the job processing times are machine independent. A solution to our problem is characterized by (i) partitioning the set of jobs into a set of accepted jobs and a set of rejected jobs, and (ii) scheduling the accepted jobs in a proportionate flow shop setting. The aim is to find a solution to minimize the sum of total weighted late work of the accepted jobs and total rejection cost of the rejected jobs. When all jobs share a common due date, we show that the single-machine case is [Formula: see text]-hard by reduction from the Subset Sum problem. When the operations of all jobs have equal processing times, we solve the case in [Formula: see text] time by reducing it into a linear assignment problem. For the general problem, we first provide a pseudo-polynomial-time algorithm via the dynamic programming method, then we convert it into a fully polynomial time approximation scheme. As a byproduct, we also resolve an open question in the literature.
本文研究了在比例流车间环境下,作业处理时间与机器无关的可选作业拒绝调度问题。我们的问题的解决方案的特点是:(i)将一组作业划分为一组接受的作业和一组拒绝的作业,以及(ii)在一个按比例的流程车间设置中调度接受的作业。目标是找到一个解,使被接受作业的总加权延迟工作和被拒绝作业的总拒绝成本之和最小。当所有作业共享一个共同的截止日期时,我们表明单机情况是[公式:见文本]-很难从子集和问题中简化。当所有作业的处理时间相等时,我们通过将其简化为线性分配问题来解决[公式:见文]时间中的情况。对于一般问题,我们首先通过动态规划方法给出一个伪多项式时间算法,然后将其转化为一个全多项式时间逼近格式。作为副产品,我们也解决了一个悬而未决的问题,在文献。
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引用次数: 0
期刊
Asia-Pacific Journal of Operational Research
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