Containers are commonly used as an effective and relatively inexpensive method for transporting goods. Unfortunately, there are often imbalances between the number of import and export containers, and some ports have a surplus of empty containers while others have a deficit. The Empty Container Simulation Game was developed to address these problems. The game is a computer role playing simulation that simulates the distribution of empty containers in order to solve empty container imbalances among ports. An optimal solution is obtained by the computer using linear programming (LP). Upon completion of the game, a player's game results are displayed along with the LP solution. The game interface was designed to provide easy access and operation. This game will serve to provide an easy understanding and planning for empty container management.

For proper ergonomic evaluation using a digital human model simulation (DHMS) system such as $RAMSIS^{(R)}$, the postures of humanoids for designated tasks need to be predicted accurately. The present study (1) evaluated the accuracy of driving postures of humanoids predicted by RAMSIS, (2) proposed a method to improve its accuracy, and (3) examined the effectiveness of the proposed method. The driving postures of 12 participants in a seating buck were measured by a motion capture system and compared with their corresponding postures predicted by RAMSIS. Significant discrepancies ($8.7^{\circ}$ to $74.9^{\circ}$) between predicted and measured postures were observed for different body parts and driving tasks. Two methods (constraints addition and user-defined posture) were proposed and their effects on posture estimation accuracy were examined. Of the two proposed methods, the user-defined posture method was found preferred, reducing posture estimation errors by 11.5% to 84.9%. Both the posture prediction accuracy assessment protocol and user-defined posture method would be of use for practitioners to improve the accuracy of predicted postures of humanoids in virtual environments.

Wireless sensor network may be installed where it is hard to access or where one has to constantly gather data without any human's monitoring. Sensors which compose a sensor network are usually small with poor battery capacities and thus energy-efficient usage is very important because of difficulties in replacing or recharging the batteries to make the lifetime of the whole sensor network longer. LEACH protocol, a well-known hierarchical routing protocol, may resolve this problem by distributing the role of cluster header evenly to the sensor nodes in the whole area of network at each round. In this thesis, we introduce a variant of LEACH protocol which considers the distance between base station and sensors in the way that if a node is far from the base station then the probability that this node becomes a cluster header is low. Experiments to evaluate the energy efficiency and the ability to collect the information show that the proposed method in this paper has maintained much wider sensing area while keeping the energy efficiency same as LEACH.

The determination of a regression model is important in using statistical designs of experiments. Generally, the exact regression model is not known, and experimenters suppose that a certain model form will be fit. Then an experimental design suitable for that predetermined model form is selected and the experiment is conducted. However, the initially chosen regression model may not be correct, and this can result in undesirable statistical properties. We develop model-robust experimental designs that have stable prediction variance for a family of candidate regression models over a cuboidal region by using genetic algorithms and the desirability function method. We then compare the stability of prediction variance of model-robust experimental designs with those of the 3-level face centered cube. These model-robust experimental designs have moderately high G-efficiencies for all candidate models that the experimenter may potentially wish to fit, and outperform the cuboidal design for the second-order model. The G-efficiencies are provided for the model-robust experimental designs and the face centered cube.

Marine equipment makers today face a multitude of challenges including the needs of an internal system for easy management of their business processes and a collaboration system to streamline communications with the parent company, increasing product complexity and heightened requirements for information technology. In this research, a BPM-ERP system called Biz $Tower^{(R)}$ was implemented based on cloud computing for especially, small and medium marine equipment makers to standardize and visualize the entire business process from order placement to release. This system also provides their parent company with visibility into the status of orders and user can easily access the system on the web at a low price through cloud computing service. Thus far, this paper demonstrates the applicability of Biz $Tower^{(R)}$ to improve management visibility, process performance, and collaboration with the parent company for small and medium marine equipment makers.

In this paper, we present the study of a real passenger transportation system. Passenger transportation problem aims to transport passengers from bus stops to their destinations by a fleet of vehicles while satisfying various constraints such as vehicle capacity, maximum allowable riding time in a bus, and time windows at destinations. Our problem also has special issues such as mixed loading, consideration of afternoon problem together with morning problem, and transferring passengers between vehicles. Our solution approach consists of three serial procedures: bus route generation, bus scheduling, and post optimization. Efficient heuristic algorithms were developed and implemented for the procedures. The proposed solution approach has been successfully applied to several real world problem instances and could reduce about 10% to 15% of buses.

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

This paper suggests a DEA/AHP hybrid model to deal with an allocation problem of research budget for the national research lab(NRL) program. The qualitative factors are appraised by AHP model and the quantitative factors are dealt with DEA model to evaluate the performance of research activities considering tangible and intangible factors. The proposed hybrid model is applied to get the importance weight of research areas for research budget allocation of NRL program.

In logistics e-marketplaces, brokerage agents intermediate empty vehicles and freights registered by car owners and shippers. In the previous research, we proposed constant periodic/fixed matching algorithms for the logistics brokerage agents with the objective of minimizing the total transportation lead time and the transportation due date tardiness of freights(Jeong, 2004; Jeong, 2007). However, the constant type algorithms cannot consider changes in the balance status of an e-marketplace, i.e. the difference between the numbers of freights and vehicles to wait for matching, because they use non-changing matching periods and amounts. In this paper, we propose variable type algorithms for the logistics brokerage agent, in which the matching periods and amounts are changed continuously by considering the balance status between the freights and vehicles. In order to compare performance of the variable type algorithms to the previous constant type algorithms, we carried out computational experiments on various problem instances. The results show that the variable type algorithms give better performance than the constant type algorithms. We can expect that the logistics brokerage agents can improve their performance by using the proposed variable periodic/fixed matching algorithms.

Warranty claim data analysis is a useful tool for the manufacturer because it contains many useful informations regarding reliability of the product in the real-world environments. Because of the nature of uncertainty and the incompleteness of data, some bias patterns are observed on warranty claim rate known as 'spikes'. Two types of spikes are considered. One is due to manufacturing-related failures. The other is caused by customer's behavior. This paper proposes a model by considering two types of spikes. Warranty claim data is analyzed with the proposed model. To represent spikes observed on the early warranty period, we classify failures into manufacturing-related failures and usage-related failures. Uniform distribution is assumed for the time delayed to diagnose and report by customers. By reducing maximum value of the delayed time by customers, the proposed model characterizes customer's rush in the vicinity of the warranty expiration limit. Experimental results by using the real warranty claim data show that the proposed model is better than the existing one in respect to MSE(Mean Squared Error). Moreover it is expected to estimate the failure rate more realistically with proposed model because it considers the delayed time to diagnose and report by customers.

Customer needs for final products are very unpredictable because product specifications and technologies are being improved very quickly thereby their requirement level is also elevated correspondingly. In order to survive and to enhance competitiveness in the global market, many manufacturing companies are trying to find a breakthrough from collaborization. Even though they want to collaborate with others, however, they do not exactly know what kind of system they have to develop or which technology they have to use. In this paper, therefore, we first investigate status and trend of information systems and infrastructure that are essential for collaboration. We then clearly describe definition and classification of collaboration with various point of views considering collaboration pattern, timing condition of collaborative activities, organizational structure, etc. With web-based collaboration systems already developed by i-Manufacturing (Korean-style Manufacturing Innovation) project, led by Korean government from 2004, we introduce main functions and analyze collaboration types of each system. Strategically important technologies for supporting collaboration will also be illustrated by reorganizing collaborization technologies after evaluating them with respect to emergency and importance of each technology. We hope this research will provide a guideline on collaboration especially for small and medium sized manufacturing companies.

The quality of service(QoS) model should be presented with the optimal network design to effectively provide the multimedia data services between users and converged services with mobile or TV in the next-generation Internet. In specific, the method to provide differentiated services for each user is needed in the given Internet node to offer the previously negotiated QoS with the user. In this paper, the performance of the QoS enabling technologies in the differentiated services(DiffServ) network domain is analyzed. The QoS offering model and QoS metrics are presented to analyze the performance of the major scheduling algorithms. Under the real network topology and virtual service scenarios in the university, the NS-2 network simulation based on the discrete-event is performed. The results show that the ratio-based scheduling method is more effective rather than the bandwidth-assignment method.