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Efficient iterated greedy algorithm to minimize makespan for the no-wait flowshop with sequence dependent setup times

Efficient iterated greedy algorithm to minimize makespan for...

引用

2012 IEEE 16th International Conference on computer Supported Cooperative Work in Design, CSCWD 2012

作者： Xu, Tao Zhu, Xia Li, Xiaoping School of Computer Science and Engineering Southeast University 211189 Nanjing China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

ISBN: (纸本)9781467312127

In this paper, an efficient iterated greedy algorithm is proposed for the SDST (Sequence Dependent Setup Time) no-wait flowshop with makespan minimization, which is known to be NP-hard. By introducing effective operators, the Iterated Greedy algorithm is adapted to the considered problem. To improve the quality of solutions, Local Search is incorporated into the modified Iterated Greedy algorithm. The proposed algorithm is compared with BIH, GAPH1∼GAPH4, and IG-Ruiz on Taillard's instances of ssd10, ssd50, ssd100, and ssdl25. Experimental results demonstrate that the proposal outperforms BIH and GAPH1∼GAPH4. As well, the proposal is more effective than IG-Ruiz under the same computation-time criterion. © 2012 IEEE.

关键词： Local search (optimization)

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Hybrid heuristic for total flowtime minimization in no-wait flow shops

Hybrid heuristic for total flowtime minimization in no-wait ...

引用

11th International Conference on computer Supported Cooperative Work in Design, CSCWD 2007

作者： Zhu, Xia Li, Xiaoping Wang, Qian School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University Nanjing China

ISBN: (纸本)1424409632

In this paper, no-wait flow shop scheduling problem with total flowtime minimization is considered. A hybrid heuristic is proposed, which is based on PH1 (p) (presented by Aldowaisan and Allahverdi, OMEGA, 2004). A composite algorithm is adopted to generate the initial seed. Job insertion in PH1 (p) is replaced with an existing constructive heuristic. Experimental results show that the proposal outperforms PH1 (p), especially for large scale instances. ©2007 IEEE.

关键词： Scheduling

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SEAVER: Attention Reallocation for Mitigating Distractions in Language Models for Conditional Semantic Textual Similarity Measurement

SEAVER: Attention Reallocation for Mitigating Distractions i...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Li, Baixuan Fan, Yunlong Gao, Zhiqiang School of Computer Science and Engineering Southeast University Nanjing211189 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

ISBN: (纸本)9798891761681

Conditional Semantic Textual Similarity (C-STS) introduces specific limiting conditions to the traditional Semantic Textual Similarity (STS) task, posing challenges for STS models. Language models employing cross-encoding demonstrate satisfactory performance in STS, yet their effectiveness significantly diminishes in C-STS. In this work, we argue that the failure is due to the fact that the redundant information in the text distracts language models from the required condition-relevant information. To alleviate this, we propose SElf-Augmentation Via SElf-Reweighting (SEAVER), which, based solely on models' internal attention and without the need for external auxiliary information, adaptively reallocates the model's attention weights by emphasizing the importance of condition-relevant tokens. On the C-STS-2023 test set, SEAVER consistently improves performance of all million-scale fine-tuning baseline models (up to around 3 points), and even surpasses performance of billion-scale few-shot prompted large language models (such as GPT-4). Our code is available at https://***/BaixuanLi/SEAVER. © 2024 Association for Computational Linguistics.

关键词： Semantics

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Multi-Label Open Set Recognition 38

Multi-Label Open Set Recognition

引用

38th Conference on Neural information Processing Systems, NeurIPS 2024

作者： Wang, Yi-Bo Hang, Jun-Yi Zhang, Min-Ling School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

In multi-label learning, each training instance is associated with multiple labels simultaneously. Traditional multi-label learning studies primarily focus on closed set scenario, i.e. the class label set of test data is identical to those used in training phase. Nevertheless, in numerous real-world scenarios, the environment is open and dynamic where unknown labels may emerge gradually during testing. In this paper, the problem of multi-label open set recognition (MLOSR) is investigated, which poses significant challenges in classifying and recognizing instances with unknown labels in multi-label setting. To enable open set multi-label prediction, a novel approach named SLAN is proposed by leveraging sub-labeling information enriched by structural information in the feature space. Accordingly, unknown labels are recognized by differentiating the sub-labeling information from holistic supervision. Experimental results on various datasets validate the effectiveness of the proposed approach in dealing with the MLOSR problem. © 2024 Neural information processing systems foundation. All rights reserved.

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An evolutionary algorithm for no-wait flowshop problems with flowtime minimization

An evolutionary algorithm for no-wait flowshop problems with...

引用

International Conference on computer Supported Cooperative Work in Design

ISBN: (纸本)9781457703874

In this paper, no-wait flow shop scheduling problem with flowtime minimization is considered. Objective increment properties are analyzed and proved for fundamental operations of heuristics. With these properties, whether a new generated schedule is better or worse than the original one is only evaluated by objective increments, instead of completely calculating objective values as the traditional algorithms do, so that the computational time can be considerably reduced. An evolutionary algorithm (EA) is proposed for the considered problem. The initial population with two members is generated by different heuristics. After crossover, the disturb cycles which consist of a mutation operator and strengthen approaches are conducted to the offspring. EA is compared with the best-so-far algorithms SRTS, PH1p and DPSOvnd on 110 benchmark instances. Experimental results show that EA outperforms the others on effectiveness but is a little worse than DPSOvnd on efficiency. © 2011 IEEE.

关键词： Evolutionary algorithms

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An improved harmony search algorithm for blocking job shop to minimize makespan

An improved harmony search algorithm for blocking job shop t...

引用

2012 IEEE 16th International Conference on computer Supported Cooperative Work in Design, CSCWD 2012

作者： Hou, Peiying Wang, Dandan Li, Xiaoping School of Computer Science and Engineering Southeast University 211189 Nanjing China Key Laboratory of Computer Network and Information Integration Southeast University 211189 Nanjing China

ISBN: (纸本)9781467312127

In this paper, Harmony Search is applied to the blocking job shop problem with makespan minimization. According to the characteristics of the considered problem, a decoding method is introduced to generate feasible solutions. A rule is proposed to improvise new harmonies. Some approaches are developed to determine the harmony search considering rate, the pitch adjusting rate, the dynamic harmony memory. A local search is investigated to further improve quality of the solutions. Results of numerical experiments on classical benchmark instances show that the proposed algorithm can improve makespan 16.50% on average. © 2012 IEEE.

关键词： Benchmarking

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SOA-based method for cooperative tasks distribution in large-scale optimization environments

SOA-based method for cooperative tasks distribution in large...

引用

International Conference on computer Supported Cooperative Work in Design

作者： Cui, Qiuxiang Zhu, Xia Zhang, Yi Li, Xiaoping School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9781424467631

In this paper, operators are encapsulated by services in algorithms for large-scale optimization problems and the services are deployed in distributed systems. Response time is an important factor for the performance of cooperative services. The message parse time is analyzed. Initial service accessing time is the main overhead for service calling. To decrease both the initial time and the response time, SBP (Service Buffering Pool based Scheduling Algorithm) is proposed by integrating a resource pool with a cache. Appropriate number of computing resources can be determined for large-scale optimization problems after analyzing the influence of the number of computing resources on algorithms. The proposed algorithm is compared with a centralized algorithm and a distributed algorithm without cache. Experimental results show that the proposed algorithm has a lower overhead than the other two algorithms. © 2010 IEEE.

关键词： Scheduling algorithms

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Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning 41

Binary Decomposition: A Problem Transformation Perspective f...

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41st International Conference on Machine Learning, ICML 2024

作者： Hang, Jun-Yi Zhang, Min-Ling School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

Semi-supervised learning (SSL) is a classical machine learning paradigm dealing with labeled and unlabeled data. However, it often suffers performance degradation in real-world open-set scenarios, where unlabeled data contains outliers from novel categories that do not appear in labeled data. Existing studies commonly tackle this challenging open-set SSL problem with detect-and-filter strategy, which attempts to purify unlabeled data by detecting and filtering outliers. In this paper, we propose a novel binary decomposition strategy, which refrains from error-prone procedure of outlier detection by directly transforming the original open-set SSL problem into a number of standard binary SSL problems. Accordingly, a concise yet effective approach named BDMatch is presented. BDMatch confronts two attendant issues brought by binary decomposition, i.e. class-imbalance and representation-compromise, with adaptive logit adjustment and label-specific feature learning respectively. Comprehensive experiments on diversified benchmarks clearly validate the superiority of BDMatch as well as the effectiveness of our binary decomposition strategy. Copyright 2024 by the author(s)

关键词： Self-supervised learning

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Maximum margin partial label learning 7

Maximum margin partial label learning

引用

7th Asian Conference on Machine Learning, ACML 2015

作者： Yu, Fei Zhang, Min-Ling School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

Partial label learning deals with the problem that each training example is associated with a set of candidate labels, and only one among the set is the ground-truth label. The basic strategy to learn from partial label examples is disambiguation, i.e. by trying to recover the ground-truth labeling information from the candidate label set. As one of the major machine learning techniques, maximum margin criterion has been employed to solve the partial label learning problem. Therein, disambiguation is performed by optimizing the margin between the maximum modeling output from candidate labels and that from non-candidate labels. However, in this formulation the margin between the ground-truth label and other candidate labels is not differentiated. In this paper, a new maximum margin formulation for partial label learning is proposed which aims to directly maximize the margin between the ground-truth label and all other labels. Specifically, an alternating optimization procedure is utilized to coordinate ground-truth label identification and margin maximization. Extensive experiments show that the derived partial label learning approach achieves competitive performance against other state-of-the-art comparing approaches. © 2015 F. Yu & M.-L. Zhang.

关键词： Learning systems

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Direction based charging in rechargeable wireless sensor network 1

引用

4th International Conference on IoT as a Service, IoTaaS 2018

作者： Batool, Sadia Tong, Fei Li, Songyuan He, Shibo Zhejiang University Hangzhou China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing China

ISBN: (数字)9783030146573

ISBN: (纸本)9783030146566

. One of the main issues in rechargeable wireless sensor networks (RWSNs) is the stainability of network operation. Recently, wireless power transmission technology has been applied in RWSNs to transmit wireless power from chargers to sensor nodes. In this paper, we focus on how a charger changes its direction to cover different nodes for energy provisioning and, how to sense maximum data from the area of network. We intend to tackle the challenge that how to cover different nodes from each direction so that the charger can provide maximum power to maintain network performance. In this regard, a direction scheduling algorithm is proposed to fill the charging demand. Furthermore, a proposed Linear Programming based solution is proposed to determine maximum data sensing rate. The simulation results show that the proposed method performs better compared with existing methods. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2019.

关键词： Linear programming

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