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Multi-attribute group decision-making using double hierarchy hesitant fuzzy linguistic preference information

NEURAL COMPUTING & APPLICATIONS 2020年第17期32卷 14031-14045页

作者： Krishankumar, R. Ravichandran, K. S. Shyam, V. Sneha, S. V. Kar, Samarjit Garg, Harish SASTRA Univ Sch Comp Thanjavur 613401 Tamil Nadu India Natl Inst Technol Dept Math Durgapur W Bengal India Thapar Inst Engn & Technol Deemed Univ Sch Math Patiala 147004 Punjab India

Double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) is one of the successful extensions of the hesitant fuzzy linguistic term set used for describing the uncertain information in a more prominent manner for solving the group decision-making problems. In DHHFLTS, the membership functions are represented in terms of linguistic membership degrees which are a flexible structure for preference elicitation and enrich the ability for rational decision-making with complex linguistic expressions. Driven by the flexibility of DHHFLTS, in this paper, a new decision framework is developed for solving decision-making problems, which provides scientific and rational decisions based on the preference information. For it, initially, a new aggregation operator is proposed for aggregating decision-makers' preferences. Later, the importance of the attribute weights in the problems is determined by formulating a mathematical model and the COPRAS method is extended to the DHHFLTS context for prioritizing alternatives. The applicability of the presented approach is demonstrated through a numeric example related to green supplier selection. A comparative analysis with existing studies is also administered to test the effectiveness and verify the method.

关键词： COPRAS method Double hierarchy Group decision-making Maclaurin symmetric mean programming model

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A comparative study for consistency-based decision making with interval multiplicative preference relations

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INTERNATIONAL JOURNAL OF GENERAL SYSTEMS 2020年第4期49卷 400-437页

作者： Meng, Fanyong Tang, Jie BeijingWuzi Univ Sch Informat Beijing Peoples R China Cent South Univ Sch Business Changsha Peoples R China

To ensure the reasonable application and perfect the theory of decision making with interval multiplicative preference relations (IMPRs), this paper continues to discuss decision making with IMPRs. After reviewing previous consistency concepts for IMPRs, we find that Krejci's consistency concept is more flexible and natural than others. However, it is insufficient to address IMPRs only using this concept. Considering this fact, this paper researches inconsistent and incomplete IMPRs that are usually encountered. First, programming models for addressing inconsistent and incomplete IMPRs are constructed. Then, this paper studies the consensus of individual IMPRs and defines a consensus index using the defined correlation coefficient. When the consensus requirement does not satisfy requirement, a programming model for improving consensus level is built, which can ensure the consistency. Subsequently, a procedure for group decision making with IMPRs is offered, and associated examples are provided to specifically show the application of main theoretical results.

关键词： Group decision making IMPR consistency and consensus programming model correlation coefficient

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programming heterogeneous architectures using hierarchical tasks

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2023年第25期35卷

作者： Faverge, Mathieu Furmento, Nathalie Guermouche, Abdou Lucas, Gwenole Namyst, Raymond Thibault, Samuel Wacrenier, Pierre-Andre Bordeaux INP Bordeaux France LaBRI Bordeaux France Univ Bordeaux Bordeaux France Inria Bordeaux Sud Ouest Bordeaux France CNRS Bordeaux France

Task-based systems have become popular due to their ability to utilize the computational power of complex heterogeneous systems. A typical programming model used is the Sequential Task Flow (STF) model, which unfortunately only supports static task graphs. This can result in submission overhead and a static task graph that is not well-suited for execution on heterogeneous systems. A common approach is to find a balance between the granularity needed for accelerator devices and the granularity required by CPU cores to achieve optimal performance. To address these issues, we have extended the STF model in the StarPU runtime system by introducing the concept of hierarchical tasks. This allows for a more dynamic task graph and, when combined with an automatic data manager, it is possible to adjust granularity at runtime to best match the targeted computing resource. That data manager makes it possible to switch between various data layout without programmer input and allows us to enforce the correctness of the DAG as hierarchical tasks alter it during runtime. Additionally, submission overhead is reduced by using large-grain hierarchical tasks, as the submission process can now be done in parallel. We have shown that the hierarchical task model is correct and have conducted an early evaluation on shared memory heterogeneous systems using the Chameleon dense linear algebra library.

关键词： accelerator dense linear algebra GPU heterogeneous computing Multicore programming model runtime system task graph

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modelling and analysis of offshore energy hubs

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ENERGY 2022年第PartA期261卷

作者： Zhang, Hongyu Tomasgard, Asgeir Knudsen, Brage Rugstad Svendsen, Harald G. Bakker, Steffen J. Grossmann, Ignacio E. Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management Hogskoleringen 1 N-7491 Trondheim Norway SINTEF Energy Res Kolbjorn Hejes Vei 1B N-7491 Trondheim Norway Carnegie Mellon Univ Dept Chem Engn 5000 Forbes Ave Pittsburgh PA 15213 USA

Clean offshore energy hubs may become pivotal for efficient offshore wind power generation and distribution. In addition, offshore energy hubs may provide decarbonised energy supply for maritime transport, oil and gas recovery, and offshore farming, while also enabling conversion and storage of liquefied decarbonised energy carriers for export. In this paper, the role of offshore energy hubs is investigated in the transition of an offshore energy system towards zero-emission energy supply. A mixed-integer linear programming model is developed for investment planning and operational optimisation to achieve decarbonisation at minimum cost. We consider offshore wind, solar, energy hubs and subsea cables. A sensitivity analysis is conducted on CO2 tax, CO2 budget and the capacity of power from shore. The results show that: (a) a hard carbon cap is necessary for stimulating a zero-emission offshore energy system, (b) offshore wind integration and power from shore can more than halve current emissions, but offshore energy hubs with storage may be necessary for zero-emission production, and (c) at certain CO2 tax levels, the system with offshore energy hubs can potentially reduce CO2 emissions by 49% and energy losses by 10%, compared to a system with only offshore renewables, gas turbines and power from shore.

关键词： Clean offshore energy hub Sensitivity analysis Deterministic mixed-integer linear programming model

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Improving the Performance of Actors on Multi-cores with Parallel Patterns

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INTERNATIONAL JOURNAL OF PARALLEL programming 2020年第4期48卷 692-712页

作者： Rinaldi, Luca Torquati, Massimo De Sensi, Daniele Mencagli, Gabriele Danelutto, Marco Univ Pisa Comp Sci Dept Pisa Italy

The Actor-based programming model is largely used in the context of distributed systems for its message-passing semantics and neat separation between the concurrency model and the underlying hardware platform. However, in the context of a single multi-core node where the performance metric is the primary optimization objective, the "pure" Actor model is generally not used because Actors cannot exploit the physical shared-memory, thus reducing the optimization options. In this work, we propose to enrich the Actor model with some well-known Parallel Patterns to face the performance issues of using the "pure" Actor model on a single multi-core platform. In the experimental study, conducted on two different multi-core systems by using the C++ Actor Framework, we considered a subset of the Parsec benchmarks and two Savina benchmarks. The analysis of results demonstrates that the Actor model enriched with suitable Parallel Patterns implementations provides a robust abstraction layer capable of delivering performance results comparable with those of thread-based libraries (i.e. Pthreads and FastFlow) while offering a safer and versatile programming environment.

关键词： Actors Parallel patterns programming model Multi-cores

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Location and Capacity model of Charging Station for Electric Vehicles Based on Commuting Demand

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2020年第7期15卷 1089-1099页

作者： Luo, Qingyu Tian, Wanli Jia, Hongfei Jilin Univ Sch Transportat Changchun 130022 Peoples R China

For commuters, the workplace is the second most important place to be able to charge electric vehicles after their own residence. In order to satisfy the charging demand near to the workplaces of commuters, a location and capacity model for charging stations is set up with the aim of minimizing the overall cost, composed of the charging station construction cost and the generalized cost of users. The charging demand of commuting electric vehicles is divided into rigid demand and elastic demand, which depends on whether the electric vehicle has enough power to complete the rest of its daily travel requirements. By introducing a user convenience coefficient to quantify the user's charging expectation, the number of electric vehicles to be served and the demand for charging at the stations are obtained. Further, the optimal sites for charging stations and the quantities of different levels of charging facility equipped are determined by the location and capacity model. An example shows that, as the threshold of the convenience coefficient decreases, the demand for electric energy increases gradually, and the construction becomes less economical. Meanwhile, the location of the charging station is insensitive to the change of electric energy demand. The threshold value for the convenience coefficient is put forward for different planning purposes, providing a reference for planning site selection and quantity of chargers under elastic demand. (c) 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： electric vehicle charging location capacity elastic demand programming model

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Group decision making based on acceptable consistency analysis of interval linguistic hesitant fuzzy preference relations

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INFORMATION SCIENCES 2020年 530卷 66-84页

作者： Meng, Fanyong Chen, Shyi-Ming Zhang, Shaolin Beijing Wuzi Univ Sch Informat Beijing 101149 Peoples R China Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei Taiwan Cent South Univ Sch Business Changsha 410083 Peoples R China

To represent decision makers' qualitative uncertainty and hesitation judgments, interval linguistic hesitant fuzzy variables (ILHFVs) are efficient tools, which can be regarded as an expansion of interval linguistic variables (ILVs). Taking the merits of ILHFVs and preference relations, this paper focuses on group decision making (GDM) with interval linguistic hesitant fuzzy preference relations (ILHFPRs). By considering the consistency of ILHFPRs, a new definition of acceptable consistency is presented. Using the acceptable consistency index, some models are built to measure whether a given ILHFPR is acceptable consistent. If the consistency is unacceptable, some models are constructed to derive acceptable consistent ILHFPRs by considering the total adjustment and the number of adjusting ILVs. In order to cope with incomplete ILHFPRs, some models for obtaining the values of unknown ILVs are proposed. For GDM with ILHFPRs, an index for measuring the consensus degree of ILHFPRs is proposed. When ILHFPRs do not meet the requirement of the consensus, some models for enhancing the consensus degree are proposed. According to the analysis of acceptable additive consistency and consensus of ILHFPRs, a new method for GDM with ILHFPRs is proposed. In order to show the merits of the proposed GDM method, an application example is used. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Group decision making Acceptable consistency ILHFPR programming model

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Energy-Aware Self-Adaptation for Application Execution on Heterogeneous Parallel Architectures

IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING

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IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING 2020年第1期5卷 81-94页

作者： Kavanagh, Richard Djemame, Karim Ejarque, Jorge Badia, Rosa M. Garcia-Perez, David Univ Leeds Sch Comp Leeds LS2 9JT W Yorkshire England Barcelona Supercomp Ctr BSC Barcelona 08034 Spain Spanish Natl Res Council IIIA CSIC Artificial Intelligence Res Inst Bellaterra 08193 Spain Atos Madrid 28037 Spain

Hardware in High Performance Computing environments in recent years have increasingly become more heterogeneous in order to improve computational performance. An additional aspect of such systems is the management of power and energy consumption. The increase in heterogeneity requires middleware and programming model abstractions to eliminate additional complexities that it brings, while also offering opportunities such as improved power management. In this paper, we explore application level self-adaptation including aspects such as automated configuration and deployment of applications to different heterogeneous infrastructure and for their redeployment. This therefore not only mitigates complexities associated with heterogeneous devices but aims to take advantage of the heterogeneity. The overall result of this paper is a self-adaptive framework that manages application Quality of Service (QoS) at runtime, which includes the automatic migration of applications between different accelerated infrastructures. Discussion covers when this migration is appropriate and quantifies the likely benefits.

关键词： Task analysis Runtime Computer architecture Quality of service Hardware Monitoring Power demand Self-adaptation energy modelling programming model heterogeneous hardware architectures application deployment

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AceMesh: a structured data driven programming language for high performance computing

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CCF TRANSACTIONS ON HIGH PERFORMANCE COMPUTING 2020年第4期2卷 309-322页

作者： Chen, Li Tang, Shenglin Fu, You Gao, Xiran Guo, Jie Jiang, Shangzhi Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Shandong Univ Sci & Technol Qingdao Peoples R China

Asynchronous task-based programming models are gaining popularity to address the programmability and performance challenges of contemporary large scale high performance computing systems. In this paper we present AceMesh, a task-based, data-driven language extension targeting legacy MPI applications. Its language features include data-centric parallelizing template, aggregated task dependence for parallel loops. These features not only relieve the programmer from tedious refactoring details but also provide possibility for structured execution of complex task graphs, data locality exploitation upon data tile templates, and reducing system complexity incurred by complex array sections. We present the prototype implementation, including task shifting, data management and communication-related analysis and transformations. The language extension is evaluated on two supercomputing platforms. We compare the performance of AceMesh with existing programming models, and the results show that NPB/MG achieves at most 1.2X and 1.85X speedups on TaihuLight and TH-2, respectively, and the Tend_lin benchmark attains more than 2X speedup on average and attain at most 3.0X and 2.2X speedups on the two platforms, respectively.

关键词： High performance computing programming model MPI Task parallel Data driven Task dependence

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Analysis of the consistency and consensus for group decision-making with interval-valued intuitionistic fuzzy preference relations

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COMPUTATIONAL & APPLIED MATHEMATICS 2020年第3期39卷 1-35页

作者： Zhang, Shaolin Meng, Fanyong Cent South Univ Sch Business Changsha 410083 Peoples R China

This paper aims to offer a new group decision-making (GDM) method based on interval-valued intuitionistic fuzzy preference relations (IVIFPRs). To furnish this goal, a new additive consistency definition of IVIFPRs is first proposed. Then, a programming model is built to check the additive consistency of IVIFPRs. For incomplete IVIFPRs, two programming models are constructed, which aim at maximizing the consistency and minimizing the uncertainty of missing information. To achieve the minimum total adjustment, a goal programming model is established to repair inconsistent IVIFPRs. Considering the consensus, a programming model for improving the consensus degree is established, which permits different IVIFVs to have different adjustments and makes individual IVIFPRs have the smallest total adjustment to remain more original information. Based on these results, a consistency- and consensus-based GDM method is proposed. At length, a practical example for screening new majors of a private college in China is offered to illustrate the feasibility and efficiency of proposed method.

关键词： Group decision-making IVIFPR Additive consistency and consensus programming model

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