• Journal of Technology Innovation
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• v.16 no.1
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• pp.107-139
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• 2008

We studied how to achieve successful implementation of massive research and development projects requiring collaboration among industries, universities and government-supported research institute. We have set up an engineering process innovation model to be deemed most adequately for all practical purposes, relying on the theoretical studies on the merits and analysis of the effect of the information system based on Milestone Management, Work Breakdown Structures and Web, which is known to be effective for research project (schedule) management and the objective management, and implemented a real-world web-based project objective management system. After a review of various R & D Project Schedule Management methods, we found that this information system was very compatible with project objective management. This project objective management information system carries out research and development projects effectively and efficiently, getting together in cyber-space and sharing information, and has been equipped with an Early Warning Subsystem to allow for pre-analysis and timely response to potential problems arising from the course of the project. The system also contains an Executive Information System that in real time, automatically provides the management information required by managers with the rate of project progress (achievement, fulfillment and delay). Lastly, actual progress can be cross-checked through both on-line objective management on the web-based information system and design review meeting held on site, to improve the efficiency and validity of the information system. Moreover, overall effect was analyzed through questionnaires on how well the system and generated information meet requirements and on the ultimate impact of the system upon objective management and communication. The questionnaire on the system effect revealed that the information system was useful to objective management and communication, and that the quality of the system was more than acceptable as well.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.352-368
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• 2021

Sign-in point of interest (POI) are extremely sparse in location-based social networks, hindering recommendation systems from capturing users' deep-level preferences. To solve this problem, we propose a content-aware POI recommendation algorithm based on a convolutional neural network. First, using convolutional neural networks to process comment text information, we model location POI and user latent factors. Subsequently, the objective function is constructed by fusing users' geographical information and obtaining the emotional category information. In addition, the objective function comprises matrix decomposition and maximisation of the probability objective function. Finally, we solve the objective function efficiently. The prediction rate and F1 value on the Instagram-NewYork dataset are 78.32% and 76.37%, respectively, and those on the Instagram-Chicago dataset are 85.16% and 83.29%, respectively. Comparative experiments show that the proposed method can obtain a higher precision rate than several other newer recommended methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.335-352
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• 2023

When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3501-3523
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• 2017

It is a classical integer optimization difficulty to design an optimal selection scheme in cooperative relay networks considering co-channel interference (CCI). In this paper, we solve single-objective and multi-objective relay selection problem. For the single-objective relay selection problem, in order to attain optimal system performance of cooperative relay network, a novel quantum differential evolutionary algorithm (QDEA) is proposed to resolve the optimization difficulty of optimal relay selection, and the proposed optimal relay selection scheme is called as optimal relay selection based on quantum differential evolutionary algorithm (QDEA). The proposed QDEA combines the advantages of quantum computing theory and differential evolutionary algorithm (DEA) to improve exploring and exploiting potency of DEA. So QDEA has the capability to find the optimal relay selection scheme in cooperative relay networks. For the multi-objective relay selection problem, we propose a novel non-dominated sorting quantum differential evolutionary algorithm (NSQDEA) to solve the relay selection problem which considers two objectives. Simulation results indicate that the proposed relay selection scheme based on QDEA is superior to other intelligent relay selection schemes based on differential evolutionary algorithm, artificial bee colony optimization and quantum bee colony optimization in terms of convergence speed and accuracy for the single-objective relay selection problem. Meanwhile, the simulation results also show that the proposed relay selection scheme based on NSQDEA has a good performance on multi-objective relay selection.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.925-930
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• 2005

In this paper, evolutionary multi-objective selection method of RBF networks structure is considered. The candidates of RBF network structure are encoded into the chromosomes in GAs. Then, they evolve toward Pareto-optimal front defined by several objective functions concerning with model accuracy and model complexity. An ensemble network constructed by such Pareto-optimal models is also considered in this paper. Some numerical simulation results indicate that the ensemble network is much robust for the case of existence of outliers or lack of data, than one selected in the sense of information criteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2711-2733
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• 2018

Minimizing power consumption in bandwidth limited optical traffic grooming networks is presented as a two-objective optimization problem. Since the main objective is to route a connection, the network throughput is maximized first, and then the minimum power consumption solution is found for this maximized throughput. Both transparent IP over WDM (Tp-IPoWDM) and translucent IP over WDM (Tl-IPoWDM) network may be applied to examine such bi-objective algorithms. Simulations show that the bi-objective algorithms are more energy-efficient than the single objective algorithms where only the throughput is optimized. For a Tp-IPoWDM network, both link based ILP (LB-ILP) and path based ILP (PB-ILP) methods are formulated and solved. Simulation results show that PB-ILP can save more power than LB-ILP because PB-ILP has more path selections when lightpath lengths are limited. For a Tl-IPoWDM network, only PB-ILP is formulated and we show that the Tl-IPoWDM network consumes less energy than the Tp-IPoWDM network, especially under a sparse network topology. For both kinds of networks, it is shown that network energy efficiency can be improved by over-provisioning wavelengths, which gives the network more path choices.

• International Commerce and Information Review
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• v.10 no.2
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• pp.117-139
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• 2008

This study examines the determinants of trade show performance of export-oriented small and medium enterprises(SMEs). In this regard, the trade show performance is categorized into two dimensions, such as sales objective performance vs. non-sales objective performance Based on the analysis of 116 exporters participated in trade show held in DaeGu EXCO, it is found that the roles of the show organizers play more important roles in both the sales objective performance and the non-sales objective performance than the roles of the exhibitors do. It is also interesting to find that export experience has a negative influence on both the sales objective performance and the non-sales objective performance. These results suggest that trade show organizers should provide high service quality so as to enhance the trade show performance of exhibitors.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.511-513
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• 2003

멀티미디어 서비스의 증가로 다양한 QoS(Quality of Service) 파라미터를 보장하는 멀티캐스트 라우팅 알고리즘이 필요하게 되었다. 이러한 멀티캐스트 라우팅에서 고려해야 하는 각각의 QoS 파리미터와 비용과의 관계는 Trade-off 관계에 있으며, 이들을 동시에 최적화하는 멀티캐스트 라우팅 문제는 다목적 최적화 문제(Multi-Objective Optimization Problem: MOOP)에 속하는 어려운 문제이다. 다목적 최적화 문제의 목표는 다양한 파레토 최적해(Pareto Optimal Solution)를 찾는데 있으며, 이를 해결하기 위해서 본 논문에서는 다목적 유전자 알고리즘(Multiple Objective Genetic Algorithms： MOGA)을 적용하였다.