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computational experiment-Based Evaluation on Context-Aware O2O Service Recommendation

IEEE TRANSACTIONS ON SERVICES COMPUTING 2019年第6期12卷 910-924页

作者： Xue, Xiao Han, Hongfang Wang, Shufang Qin, Cheng-zhi Henan Polytech Univ Sch Comp Sci Jiaozuo 454000 Henan Peoples R China

O2O (online to offline) service recommendation is a typical context-aware service application, which needs to provide the most suitable services to customers in time according to their user profile and current context. By means of composing various data sources, different O2O service recommendation strategies can be customized, which may lead to great performance difference. Incorrect or non-real-time service recommendation would not work well and even cause negatives consequences. As a result, how to evaluate the performance of different O2O service recommendation strategies and select the most suitable one has become a key problem in the field. Due to the diversity and the variability of context events, as well as the economic, legal, and ethical impact, it is difficult or even impossible for traditional methods to realize comprehensive evaluation of various service strategies. Based on the background, this paper proposes a computational experiment-based evaluation method of O2O service recommendation strategies, which mainly consists of three parts: customization of O2O service strategies, modeling of experiment system, and execution of experiment evaluation. As a case study, the method was applied to Food O2O service. Three kinds of service strategies were compared respectively under two different market environments. experiment results show that the proposed evaluation method is effective.

关键词： Context awareness computational modeling Business Context modeling Context-aware services Object recognition Meteorology O2O service recommendation Context-aware service Service strategy computational experiment Performance evaluation

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computational experiment Research on the Equalization-Oriented Service Strategy in Collaborative Manufacturing

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2018年第2期11卷 369-383页

作者： Xue, Xiao Kou, Yan-Min Wang, Shu-Fang Liu, Zhi-Zhong Henan Polytech Univ Sch Comp Sci Jiaozuo Henan Peoples R China Henan Polytech Univ Wang Sch Econ Management Jiaozuo Henan Peoples R China Henan Polytech Univ Coll Comp Sci & Technol Jiaozuo Henan Peoples R China

In the framework of Industry 4.0, collaborative manufacturing across different supply chains is one of the most important business models. In order to avoid the uneven distribution of service requirements among service providers (i.e., non-equalization phenomenon), a lot of service strategies with different characteristics can be taken as candidate solutions to adjust the matching between service providers and service consumers. Based on the background, how to identify the application conditions of various service strategies in complex environment has become a serious challenge in the field. To solve this problem, the computational experiment-based evaluation method is proposed in this paper, including customization of service strategy, construction of experiment system, and experiment analysis of service strategy. In this paper, three possible service strategies are built to deal with the non-equalization phenomenon, i.e., non-equalization strategy, equalization strategy, collaborative equalization strategy. experiment results show that: collaborative equalization strategy can effectively enhance the service utilization rate and reduce the completion time in short supply environment;equalization strategy is the optimal one in oversupply market environment. This case study can show that the proposed method is feasible and the result is satisfactory.

关键词： Industry 4.0 collaborative manufacturing equalization-oriented services strategy computational experiment

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computational experiment of Service Policy in Collaborative Procurement 11

Computational Experiment of Service Policy in Collaborative ...

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11th IEEE International Conference on e-Business Engineering (ICEBE)

作者： Xue, Xiao Wang, Shufang Henan Polytech Univ Sch Comp Sci & Technol Jiaozuo Henan Peoples R China Henan Polytech Univ Sch Econ & Management Jiaozuo Henan Peoples R China

ISBN: (纸本)9781479965632

Companies are aware of the benefits of developing industrial clusters, and spend a great deal of time and money attempting to develop these relationships. Yet, the traditional techniques for identifying these relationships, Cluster Supply Chains (CSCs), have strong theoretical antecedents but seem to have little traction in the field. We believe this is because the standard techniques fail to capture evolution over time, nor provide useful intervention measures to reach goals. To address these problems, we introduce an agent-based computational experiment approach to evaluate CSCs, which explicitly accounts for dynamic change in the procurement process. We evaluate the procurement problem under different service charge strategies. These results will help us to understand the evolution mechanism and related phenomena, and provide valuable decision support applications to industry.

关键词： Cluster Supply Chain (CSC) collaboration procurement agent-based modeling computational experiment

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HOW TASK ALLOCATION STRATEGY AFFECTS TEAM PERFOR- MANCE： A computational experiment

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Journal of Systems Science and Systems Engineering 2018年第5期27卷 656-676页

作者： Shaoni Wang Yanzhong Dang Jiangning Wu Institute of Systems Engineering Dalian University of Technology Dalian 116024 China

This paper studies how to determine task allocation schemes according to the status and require-ments of various teams, to achieve optimal performance for a knowledge-intensive team （KIT）, whichis different from traditional task assignment. The way to allocate tasks to a team affects task processingand, in turn, influences the team itself after the task is processed. Considering the knowledge require-ment of tasks as a driving force and that knowledge exchange is pivotal, we build a KIT system modelbased on complex adaptive system theory and agent modeling technology, design task allocation strat-egies （TASs） and a team performance measurement scale utilizing computational experiment, and an-alyze how different TASs impact the different performance indicators of KITs. The experimental re-sults show the recommend TAS varies under different conditions, such as the knowledge levels ofmembers, team structures, and tasks to be assigned, particularly when the requirements to the team aredifferent. In conclusion, we put forward a new way of thinking and methodology for real task alloca-tion problems and provide support for allocation decision makers.

关键词： Knowledge intensive team (KIT) task allocation strategies (TASs) knowledge exchange team performance computational experiment

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Social Learning Evolution (SLE): computational experiment-Based Modeling Framework of Social Manufacturing

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2019年第6期15卷 3343-3355页

作者： Xue, Xiao Wang, Shufang Zhang, Lejun Feng, Zhiyong Guo, Yaodan Tianjin Univ Sch Comp Software Tianjin 300350 Peoples R China Henan Polytech Univ Jiaozuo 454000 Henan Peoples R China Yangzhou Univ Coll Informat Engn Yangzhou 225009 Jiangsu Peoples R China

As a new form of manufacturing industry in the Internet era, social manufacturing has its inherent "socialcyber" complexity: the source of manufacturing service is social, and such sociality aggravates the diversity, uncertainty, and dynamics of service supply. This poses new challenges to the service matching between supply-side and demand-side. In order to meet this challenge, it is necessary to conduct a complexity analysis of social manufacturing. Traditional researches mainly rely on data statistics and macro analysis, in which there are difficulties in clearly identifying the links between various impact factors and macro evolution phenomena. In order to change such a situation, this paper proposes a modeling framework of social manufacturing from the aspect of social learning evolution (SLE), including individual evolution model, organizational learning model, and social learning model. Based on the SLE framework, the corresponding computational experiment system is built to analyze the complexity of social manufacturing. The performance of several evolution mechanisms in social manufacturing is simulated and compared as a case study to present the application of SLE framework. The results demonstrate that our method has a substantial promise.

关键词： Competition and cooperation computational experiment social learning evolution (SLE) social manufacturing

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Exploring the optimal granularity for market segmentation in RTB advertising via computational experiment approach

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2017年 24卷 68-83页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Inst Parallel Econ Qingdao Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Changsha Hunan Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing Peoples R China

Real Time Bidding (RTB) is a novel business model of online computational advertising, developing rapidly with the integration of Internet economy and big data analysis. It evolves the business logic of online ad-delivery from buying "ad-impressions" in websites or ad slots to directly buying the best-matched "target audiences", and thus can help advertisers achieve the precision marketing. As a critical part of RTB advertising markets, Demand Side Platforms (DSPs) play a central role in matching advertisers with their target audiences via cookie-based data analysis and market segmentation, and their segmentation strategies (especially the choice of granularity) have key influences in improving the effectiveness and efficiency of RTB advertising markets. Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. With the computational experiment approach, we designed three experimental scenarios to validate our proposed model, and the experimental results show that: 1) market segmentation has the potential of improving the total revenue of all the advertisers;2) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first and followed by a decline;3) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences to DSPs' market segmentation decisions. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Real Time Bidding Demand Side Platforms Market segmentation computational experiment

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An agent-based distributed computational experiment framework for virtual supply chain network development

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第9期41卷 4094-4112页

作者： Long, Qingqi Zhejiang Univ Finance & Econ Sch Informat Hangzhou 310018 Zhejiang Peoples R China

This paper focuses on research on virtual supply chain networks instead of real supply chain networks by making use of agent technology and computational experiment method. However, the recent research is inefficient in computational experiment modeling and lack of a related methodological framework. This paper proposes an agent-based distributed computational experiment framework with in-depth study of material flow, information flow and time flow modeling in supply chain networks. In this framework, a matrix-based formal representation method for material flow, a task-centered representation method for information flow and an agent-based time synchronization mechanism for time flow are proposed to aid building a high quality computational experiment model for a multi-layer supply chain network. In order to conduct the model, a computational experiment architecture for virtual supply chain networks is proposed. In this architecture, coordination mechanisms among agents based on material flow, information flow and time flow as well as consistency check methods for computational experiment models are discussed. Finally, an implementation architecture of the framework is given and a case of virtual supply chain network is developed to illustrate the application of the framework. The computational experiment results of the case show that the proposed framework, not only feasible but correct, has sound advantages in virtual supply chain network development, computational experiment modeling and implementation. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Agent computational experiment Virtual supply chain network

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The computational experiment and its effects on approach to learning and beliefs on physics

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COMPUTERS & EDUCATION 2011年第3期56卷 547-555页

作者： Psycharis, Sarantos Sch Pedag & Technol Educ ASPETE ASPETE Athens 14221 Greece

Contemporary instructional approaches expect students to be active producers of knowledge. This leads to the need for creation of instructional tools and tasks that can offer students opportunities for active learning. This study examines the effect of a computational experiment as an instructional tool-for Grade 12 students, using a computer simulation environment created in Java for the domain of "linear oscillations without damping". In this study we use the computational experiment as an integration of the computational science with the discovery learning method. The computational experiment supports both types of research, the exploratory as well as the inventive research, helping the learners to develop not only exploratory but also expressive models. The aim of the paper is threefold. At first we want to examine the influence of the computational experiment on students' learning performance. The other two aims are related to the investigation of the experiment's influence on students' approach to learning and their beliefs on physics. Our results indicate that there is a strong shift on students' conceptual understanding and to the consideration of the coherence of physics, as well as to the realization that physics is strongly connected to mathematics. Finally students realized that mathematics, physics and information theory are strongly connected cognitive disciplines. (c) 2010 Elsevier Ltd. All rights reserved.

关键词： ICT Programming Interactive learning environments Physics learning computational experiment

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Complexity analysis of manufacturing service ecosystem: a mapping-based computational experiment approach

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2019年第2期57卷 357-378页

作者： Xiao, Xue Wang, Shufang Zhang, Lejun Qin, Cheng-zhi Henan Polytech Univ Sch Comp Sci Jiaozuo Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci Nanjing Jiangsu Peoples R China Henan Polytech Univ Sch Business Adm Jiaozuo Peoples R China Yangzhou Univ Sch Informat Engn Yangzhou Jiangsu Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing Peoples R China Nanjing Normal Univ Jiangsu Ctr Collaborat Innovat Geog Informat Res Nanjing Jiangsu Peoples R China

The trend of servitisation is increasingly affecting manufacturing enterprises. Traditional manufacturing enterprises cannot handle the related challenges of service innovation by themselves. Recently, manufacturing service ecosystem (MSE) has been proposed to support service innovation by facilitating collaboration. The construction and development of MSE need to handle a series of complexities, such as individual complexity, interaction complexity and ecological complexity. However, it is still very difficult to clearly identify the possible effect of various influence factors on MSE evolution, which is necessary analyse the complex dynamic interactive relationship among participants, so as to maintain the sustainable and healthy development of MSE. To change such a situation, this paper proposes a mapping-based computational experiment approach to analyse the evolution of MSE. This approach has three main parts, i.e. model construction of real world, model mapping of computational system and experiment evaluation of various factors of MSE evolution. By adopting the proposed approach, several case studies are conducted to investigate the possible effect of cooperation preference on the MSE evolution in various market environments. The results demonstrate that the proposed approach is effective.

关键词： manufacturing service ecosystem (MSE) model mapping competition and cooperation computational experiment ecosystem evolution

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Objective weights with intuitionistic fuzzy entropy measures and computational experiment analysis

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APPLIED SOFT COMPUTING 2011年第8期11卷 5411-5423页

作者： Chen, Ting-Yu Li, Chia-Hang Chang Gung Univ Coll Management Dept Ind & Business Management Tao Yuan 333 Taiwan Chang Gung Univ Coll Management Grad Inst Business Adm Tao Yuan 333 Taiwan

It is important to properly assess the weights of attributes when solving multi-attribute decision problems because variations in the weights often influence the rankings of the alternatives. In this paper, we propose an alternative objective weighting method to generate objective weights based on intuitionistic fuzzy (IF) entropy measures, which depend on the nature of a decision matrix in an intuitionistic fuzzy environment. Instead of the traditional fuzzy entropy measure, which is characterized by using the discriminating power to calculate the attribute weights, the proposed approach adopts the IF entropy measure, which emphasizes the credibility of the data. The IF entropy measure applied here is derived from a geometric interpretation of intuitionistic fuzzy sets and incorporates the concept of a ratio of distance measures. We implement four distance measures in the proposed approach and compare them in a computational experiment. The experimental results indicate that different IF entropy measures used in weighting methods can generate distinct objective attribute weights. In particular, when the number of attributes increases, the discrepancy between the IF entropy measures increases. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Multi-attribute decision Intuitionistic fuzzy entropy Intuitionistic fuzzy set Objective weight computational experiment

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