• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.170-178
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• 2017

This paper proposes an improved path-planning technique based on the $A^*$ algorithm. The conventional $A^*$ algorithm only considers the optimality of the planned path and sometimes produces a path that an unmanned underwater vehicle (UUV) cannot navigate due to its dynamic constraint such as the limit of the radius of gyration. It is because that the previous method evaluate the moving cost based on the straight distance between nodes. We enhance the conventional method by evaluating the moving cost on the basis of the practically navigable trajectory, which is generated by the waypoint-tracking control of the UUV dynamics. The simulation examples indeed show the effectiveness of the proposed technique.

• Structural Engineering and Mechanics
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• v.56 no.5
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• pp.707-726
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• 2015

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.105-111
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• 2017

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers' are assumed to have the common cycle time, and a vendor manages retailers' inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor's cost, retailer's cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.136-148
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• 2015

We analyzed the effect of three different types of inventory systems for saving the total cost using simulation on the system where multiple depots and many retailers disperse on the limited area. Three types of inventory systems are single echelon system with inventory exchange and two-echelon system and the variant two-echelon system. Variant two echelon system is the two-echelon system where the inventory transshipmentsare allowed on every two stage inventory echelons. Inventories kept on every retailer are commonly used for all retailers when certain retailer has stock-out. And when all retailers are stock-out, inventories kept on every depot are commonly used for the retailers whose assigned depots are stock-out. These all three systems are simulated with the constraint of service level on wide range of parameter settings. Simulation results show that cost saving effect appear clear for single echelon system and two-echelon system when shortage cost portion and transportation cost portion becomes large respectively irrespective of depot number. Variant two echelon system seems to be superior to two other systems when transportationcost portion becomes very small. But this superiority is not proved in terms of statistics. So we may conclude that the variant two echelon system may be useless with the higher administrative efforts due to frequent inventory exchange. Also we note that the traditional two echelon system becomes inferior to two other systems in terms of statistics when service level becomes high or when demand variance becomes very large. And inventory integration effect that cost becomes saved when depot number decrease, diminishes when transportation cost or stock-out cost increases irrespective of inventory systems.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Journal of Computing Science and Engineering
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• v.4 no.2
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• pp.173-187
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• 2010

Recent technological advances in mobile communication systems have made explosive growth in the number of mobile device users worldwide. One of the most important issues in designing a mobile computing system is location management of users. The hierarchical systems had been proposed to solve the scalability problem in location management. The scalability problem occurs when there are too many users for a mobile system to handle, as the system is likely to react slow or even get down due to late updates of the location databases. In this paper, we propose a top-down clustering algorithm for hierarchical location database systems in a wireless network. A hierarchical location database system employs a tree structure. The proposed algorithm uses a top-down approach and utilizes the number of visits to each cell made by the users along with the movement information between a pair of adjacent cells. We then present a modified algorithm by incorporating the exhaustive method when there remain a few levels of the tree to be processed. We also propose a capacity constraint top-down clustering algorithm for more realistic environments where a database has a capacity limit. By the capacity of a database we mean the maximum number of mobile device users in the cells that can be handled by the database. This algorithm reduces a number of databases used for the system and improves the update performance. The experimental results show that the proposed, top-down, modified top-down, and capacity constraint top-down clustering algorithms reduce the update cost by 17.0%, 18.0%, 24.1%, the update time by about 43.0%, 39.0%, 42.3%, respectively. The capacity constraint algorithm reduces the average number of databases used for the system by 23.9% over other algorithms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1112-1120
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• 2009

In this paper, the authors introduced a new approach to find the target orbits of each satellite in order to establish a temporary reconnaissance constellation mission to minimize the average revisit time (ART) while satisfying the constraint on fuel limit. Two distinct problems are dealt with: the first is to reconnoiter the local area with discriminating fuel constraint the second is to reconnoiter ground moving target with same fuel constraint. A preliminary effort in applying a genetic algorithm to those problems has also been demonstrated through simulation study. The results show that current ARTs of each mission are reduced by 41% and 42%, respectively, by relocating the orbit of each satellite. Naturally, the final result may depend on satellite orbits, sensor characteristics, allowable fuel cost, thruster capability, and maneuver strategies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.112-123
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• 1997

The optimization techniques have been applied to versatile engineering problems for reducing manufacturing cost and for automatic design. The deterministic approaches or op5imization neglect the effects on uncertainties of design variables. The uncertainties include variation or perturbation such as tolerance band. The optimum may be useless when the constraints considering worst cases of design variables can not be satisfied, which results from constraint variation. The variation of design variables can also give rise to drastic change of performances. The two issues are related to constraint feasibility and insensitive performance. Robust design suggested in the present study is developed to gain an optimum insensitive to variation on design variables within feasible region. The multiobjective function is composed to the mean and the standard deviation of original objective function, while the constraints are supplemented by adding penalty term to original constraints. This method has a advantage that the second derivatives of the constraints are not required. A mathematical problem and several standard problems for structural optimization are solved to check out the usefulness of the suggested method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1234-1242
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• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.1
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• pp.18-28
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• 2002

This research is a preliminary empirical investigation to segment the green tourism market by intention, which is a major precedent variable determining the behavior(i.e., participation in green tourism). Then, characteristics of each segmented group such as their socio-demographic variables, green tourism attitude, types of attractions they want to be provided in destination, and constraints to participate in green tourism were compared to give information useful for green tourism managers. Data was collected by a polling agency on a total of 608 residents of Seoul, who would be potential green tourists. Three green tourist groups were identified by intention to participate. The results showed that only gender among socio-demographic variables, two constraint factors, green tourism attitude, and s]me attractions were statistically significant. It is worth noticing, however, that there was no difference in green tourism attitude between the two groups that have the strongest and the weakest intention to participate in green tourism. This result means that the green tourism attitude does not always influence positively on the formation of intention. Perceived behavioral control construct such as cost may played an important role in lowering intention to visit. Based on the findings, several marketing strategies were suggested such as identification of target market and inducing potential green tourists to participate.