• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4329-4348
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• 2019

Mobile cloud computing (MCC) can offload heavy computation from mobile devices onto nearby cloudlets or remote cloud to improve the performance as well as to save energy for these devices. Therefore, it is essential to consider how to achieve efficient computation offloading with constraints for multiple users. However, there are few works that aim at multi-objective problem for multiple users. Most existing works concentrate on only single objective optimization or aim to obtain a tradeoff solution for multiple objectives by simply setting weight values. In this paper, a multi-objective optimization model is built to minimize the average energy consumption, time and cost while satisfying the constraint of bandwidth. Furthermore, an improved multi-objective optimization algorithm called D-NSGA-II-ELS is presented to get Pareto solutions with better convergence and diversity. Compared to other existing works, the simulation results show that the proposed algorithm can achieve better performance in terms of energy consumption, time and cost while satisfying the constraint of the bandwidth.

• Steel and Composite Structures
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• v.51 no.6
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• pp.647-659
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• 2024

Given the increased interest in enhancing structural sustainability, the current study sought to apply multiobjective optimization to a footbridge with a steel-concrete composite I-girder structure. It was considered as objectives minimizing the cost for building the structure, the environmental impact assessed by CO2 emissions, and the vertical accelerations created by human-induced vibrations, with the goal of ensuring pedestrian comfort. Spans ranging from 15 to 25 meters were investigated. The resistance of the slab's concrete, the thickness of the slab, the dimensions of the welded steel I-profile, and the composite beam interaction degree were all evaluated as design variables. The optimization problem was handled using the Multiobjective Harmony Search (MOHS) metaheuristic algorithm. The optimization results were used to generate a Pareto front for each span, allowing us to assess the correlations between different objectives. By evaluating the values of design variables in relation to different levels of pedestrian comfort, it was identified optimal values that can be employed as a starting point in predimensioning of the type of structure analyzed. Based on the findings analysis, it is possible to highlight the relationship between the structure's cost and CO2 emission objectives, indicating that cost-effective solutions are also environmentally efficient. Pedestrian comfort improvement is especially feasible in smaller spans and from a medium to a maximum level of comfort, but it becomes expensive for larger spans or for increasing comfort from minimum to medium level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2396-2402
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• 2015

Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.89-96
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• 2001

Agent-mediated electronic markets have been a grow-ing area of agent research and developmen tin recent year. There exist a lot of e-commerce sites on the In-ternet(e.g. Priceline, com, Amazon, com etc). These e-commerce site have proposed new business models for effective and efficient commerce activity. Intelli-gent agents have been studied very widely in the field of artificial intelligence, For purpose of this paper, an agent can act autonomously and collaboratively in a network environment on behalf of its users. It is hard for people to effectively and efficiently monitor, buy, and sell at multiple e-commerce sites. If we intro-duce agent technologies into e-commerce systems, we can expect to further enhance the intelligence of their support. In this paper, we propose a new coopera-tion mechanism among seller agents based on exchang-ing their goods in our agent-mediated electronic market system. G-Commerce. On G-Commerce, seller agents and buyer agents negotiate with each other. In our model, seller agents cooperatively negotiate in order to effectively sell goods in stock. Buyer agents coopera-tively form coalitions in order to buy goods based an discount proices. Seller agent's negotiation goods. Our current experiments show that exchanging mechanism enables seller agents to effectively sell goods in stock. Also, we present the Pareto optimality of our exchang-ing mechanism.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.124-145
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• 2014

Market failure occurs when Pareto efficiency is not achieved through market mechanism. In order to solve this problem, government intervene market; paying great attention to the optimum state of resource allocation. However, as the size of government investment in R&D goes up, many professionals emphasize the importance in efficient management system. This work is the result of exploratory study to look into life-cycle management of governmental R&D program. Literature reviews and empirical research on governmental R&D programs elicit improvements for effective life-cycle management of governmental R&D program as follows: consistent discrimination between capital expenditure and recurring expenditure, dual management system by spending properties, implementing total cost management system in capital expenditure, and discrimination between preliminary feasibility study with confirming total program cost in recurring expenditure.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.963-973
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• 2005

Increasing attention is being recently devoted to various problems inherent in the topological design of networks systems. The topological structure of these networks can be based on service centers, terminals (users), and connection cable. Lately, these network systems are well designed with tiber optic cable, because the requirements from users become increased. But considering the high cost of the fiber optic cable, it is more desirable that the network architecture is composed of a spanning tree. In this paper, we present a GA (Genetic Algorithm) for solving bicriteria network topology design problems of wide-band communication networks connected with fiber optic cable, considering the connection cost, average message delay, and the network reliability We also employ the $Pr\ddot{u}fer$ number (PN) and cluster string in order to represent chromosomes. Finally, we get some experiments in order to certify that the proposed GA is the more effective and efficient method in terms of the computation time as well as the Pareto optimality.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.43-52
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• 2007

As the number of public Web Services increases, there will be many services with the same functionality. These services. however, will vary in their QoS properties, such as price, response time and availability, and it is very important to choose a best service while satisfying given QoS constraints. This paper brings parallel branching and response time constraint of business processes into focus and investigates several service selection plans based on multidimensional multiple choice Knapsack model. Specifically. proposed in the paper are a plan with response time constraints for each execution flow, a plan with a single constraint over the whole service types and a plan with a constraint on a particular execution path of a composite Web Services. Experiments are conducted to observe the performance of each plan with varying the number of services, the number of branches and the values of response time constraint. Experimental results show that reducing the number of candidate services using Pareto Dominance is very effective and the plan with a constraint over the whole service types is efficient in time and solution quality for small to medium size problems.

• KDI Journal of Economic Policy
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• v.36 no.4
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• pp.1-32
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• 2014

Auction is widely used in allocation and procurement of resources due to its desirable properties: efficiency and revenue maximization. It is well-known, however, that auction may fail to achieve efficiency when allocative externalities exist. Such a result may happen in the auction of the resources that are very scarce, for example, radio spectrum. This is because allocation of the resources has effects on competition of the firms in the aftermarket, and thus a firm that utilizes the resources less efficiently may make a higher bid to lessen competition. This paper shows first that efficient allocation may not be achieved by auction even when the number of bidders is 2, while it is shown in the literature that auction may result in inefficient allocation when the number of bidders is greater than or equal to 3. There exist 2 firms, who make a bid to win the scarce resources that increase the value or decrease the production cost of their own product. After the auction ends, the firms engage in Bertrand competition on the Hotelling line. Inefficient allocation may happen even under the second-price auction rule, and it happens only when the firms are different in the initial value or the initial cost of their products as well as in the value of the auctioned resources. The firm who has been the leader loses a large portion of the market if it fails to win the auction, and thus makes a high bid even when the other firm can use the resources more efficiently. Allocative efficiency Pareto improves when the smaller firm's bid counts more than the leader's bid. This paper suggests a modified rule that the smaller firm wins the auction when its bid multiplied by some constant is greater than the leader's bid. The multiplier can be calculated from the market shares. It is equal to 1 when the two firms are the same, and is increasing in the leader's market share. Allocation is efficient in a strictly larger set of parameters under the modified rule than under the standard second-price auction rule.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.108-118
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• 2014

On the optimization design problem using surrogate model, it requires considerable number of sampling points to construct a surrogate model which retains the accuracy. As an alternative to reduce construction cost of the surrogate model, Variable-Fidelity Modeling(VFM) technique, where correct high fidelity model based on the low fidelity surrogate model is introduced. In this study, hierarchical kriging model for variable-fidelity surrogate modeling is used and an optimization framework with multi-objective genetic algorithm(MOGA) is presented. To prove the feasibility of this framework, airfoil design optimization process is performed for the transonic region. The parameters of PARSEC are used to design variables and the optimization process is performed in case of varying number of grid and varying fidelity. The results showed that pareto front of all variable-fidelity models are similar with its single-level of fidelity model and calculation time is considerably reduced. Based on computational results, it is shown that VFM is a more efficient way and has an accuracy as high as that single-level of fidelity model optimization.