• Korean Management Science Review
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• v.21 no.1
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• pp.39-55
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• 2004

Efficient crew scheduling for cockpit crew is important in airline industry due to operational safety and cost associated with the flight duty time. Because of complexity of regulations imposed to the cockpit crew. it is complicated to generate an efficient schedule. Schedule of cockpit crew can be generated through two steps; selecting of flight patterns. and scheduling of them to the specific time horizon. Heuristic method is developed and applied with massive data in a limited time of computation. A set of flight patterns is selected from all possible flight patterns. which are generated by composing the flight leg based on regulations. by using the set partitioning problem with objective function of oversea stay cost. The selected set of flight patterns found at the first step is allocated to 4 week crew schedule to minimize the variance of total fight time assigned to each crew. The crew schedules obtained are evaluated and compared with the ones currently used in one of major airline company.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.97-112
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• 2000

The basic idea of case-based reasoning is to solve a new problem using the previous problem-solving experiences. In this research we develop a case-based reasoning system for equipment malfunction diagnosis. We first divide the case base into clusters using the case-based clustering technique. Then we develop an appropriate case-based diagnostic system for each cluster. In other words for individual cluster a different case-based diagnostic system which uses different weights for attributes is developed. As a result multiple case-based reasoning system are operating to solve a diagnostic problem. In comparison to the performance of the single case-based reasoning system our system reduces the computation time by 50% and increases the accuracy by 5% point.

• Management Science and Financial Engineering
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• v.3 no.1
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• pp.1-14
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• 1997

We address the problem of determining the sequence of a vehicle with fixed capacity to visit n nodes at which a predetermined amount is picked up and/or delivered. The objective is to minimize the total travel distance of the vehicle, while satisfying the pick-up/delivery requirements and feasibility at all nodes. Existing methods for the problem allows the vehicle to visit a node twice, which is impractical in many real situations. We propose a heuristic algorithm, in which every node is visited exactly once. Computational results using random problems indicate that the proposed heuristic outperforms existing methods for practical range of the number of nodes in reasonable computation time.

• Steel and Composite Structures
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• v.24 no.3
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• pp.369-382
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• 2017

This study investigates the reliability of the performance levels of moment resisting steel frames subjected to lateral loads such as wind and earthquake. The reliability assessment has been performed with respect to three performance levels: serviceability, damageability, and ultimate limit states. A four-story moment resisting frame is used as a typical example. In the reliability assessment the uncertainties in the loadings and in the capacity of the frame have been considered. The wind and earthquake loads are assumed to have lognormal distribution, and the frame resistance is assumed to have a normal distribution. In order to obtain an appropriate limit state function a linear relation between the loading and the deflection is formed. For the reliability analysis an algorithm has been developed for determination of limit state functions and iterations of the first order reliability method (FORM) procedure. By the method presented herein the multivariable analysis of a complicated reliability problem is reduced to an S-R problem. The procedure for iterations has been tested by a known problem for the purpose of avoiding convergence problems. The reliability indices for many cases have been obtained and also the effects of the coefficient of variation of load and resistance have been investigated.

• Korean Management Science Review
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• v.5 no.1
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• pp.56-70
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• 1988

In this study, We reviewed the solution methods (for the heuristic and optimization method) for the single-item dynamic lot-sizing problem, and improved the efficiency (speed and optimality) of the conventional heuristic method by utilizing the inventory decomposition property. The iventory decomposition property decomposes the given original problem into several independent subproblems without violating the optimality conditions. Then we solve each decomposed subproblems by using the conventional heuristics such as LTC, LUC, Silver-Meal etc. For testing the efficiency of the proposed decomposition method, we adopted the data sets given in Kaimann, Berry and Silver-Meal. The computational results show that the suggested problem solving framework results in some promising effects on the computation time and the degree of optimality.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1034-1038
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• 2005

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and develops an improved genetic algorithm (IGA) to solve it. Each individual in the IGA represents a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. Experimental results show that the proposed method leads to a speedup of 83 on $320{\times}240$ images compared to the traditional exhaustive search method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2030-2035
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• 2005

In this paper, we study the distributed coordination of a set of synchronous, anonymous, memoryless mobile robots that can freely move on a two-dimensional plane but are unable to communicate directly. Based on this model, we analyze the application problem that consists in having a group of robots form a barricade line to protect from car traffic a crowd of demonstrators parading on the street. For the sake of robustness, we privilege fully decentralized solutions to the problem. In particular, we give a self-stabilizing distributed algorithm to address the problem, in this presentation

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.147-151
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• 1991

In this paper a time-optimal path planning scheme for the multiple robot manipulators will be proposed by using hopfield neural network. The time-optimal path planning, which can allow multiple robot system to perform the demanded tasks with a minimum execution time and collision avoidance, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to rearrange the problem as MTSP(Multiple Travelling Salesmen Problem) and then apply the Hopfield network technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning of the multiple robots by using Hopfield neural network. The effectiveness of the proposed method is demonstrated by computer simulation.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1070-1073
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• 2002

This study presents a parallel branch-and-bound (PBAB) method for traveling salesman problem (TSP). The PBAB method adopts intermediate form of central control and distributed control in terms of the lightness of the master process's role. Compared with fully distributed control, the control scheme involves less concentration of communication on the master. Moreover, in order to reduce the influence of communication, the worker is composed of a computation thread and a communication thread. The multithreadness realizes the almost blocking free communications on the master. We implement the proposed PBAB method on a network of PCs, which consists of one master and up to 16 workers. We experiment five TSP instances. The results shows that the efficiency increases with the problem size.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1733-1739
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• 2006

This paper is concerned with multi-objective vehicle routing problem(VRP), in which objective of this problem is to minimize the total operating time of vehicles and the total tardiness of customers. A mixed integer programming formulation and a heuristic for practical use are suggested. The heuristic is based on the route-perturbation and route-improvement method(RPRI). Performances are compared with other heuristic appeared in the previous literature using the modified bench-mark data set. It is shown that the suggested heuristic give good solution within a short computation time by computational experiment.