• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.127-138
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• 1993

The Production Switching Heuristic (PSH) develope dby Mellichamp and Love (1978) has been suggested as a more realistic, practical and intuitively appealing approach to aggregate production planning (APP). In this researh, PSH has been modified to present a more sophisticated open grid search procedure for solving the APP problem. The effectiveness of this approach has been demonstrated by determining a better near-optimala solution to the classic paint factory problem. The performance of the modified production switching heuristic is then compared in the context of the paint factory problem with results obtained by other prominent APP models including LDR, PPP, and PSH to conclude that the modified PSH offers a better minimum cost solution than the original PSH model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.812-815
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• 1996

In this paper, we consider the optimal control problem based on Discrete Event Dynamic Systems(DEDS) in the Temporal Logic framework(TLF) which have studied for a convenient modeling technique. The TLF is enhanced with objective functions(event cost indices) and a measurement space is also defined. Our research goal is the design of the optimal controller for DEDSs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.25-33
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• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• IE interfaces
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• v.11 no.1
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• pp.183-190
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• 1998

This paper is concerned with the bicriteria vehicle routing problems with time window constraints(BVRPTW). The BVRPTW is to determine the most favorable vehicle routes that minimize the total vehicle travel time and the total customer wait time which are, more often than not, conflicting. We construct a linear goal programming (GP) model for the BVRPTW and propose a heuristic algorithm to relieve a computational burden inherent to the application of the GP model. The heuristic algorithm consists of a parallel insertion method for clustering and a sequential linear goal programming procedure for routing. The results of computational experiments showed that the proposed algorithm finds successfully more favorable solutions than the Potvin an Rousseau's method that is known as a very good heuristic for the VRPs with time window constraints, through the change of target values and the decision maker's goal priority structure.

• Korean Management Science Review
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• v.11 no.1
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• pp.91-106
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• 1994

In mixed model assembly lines, products are assembled seqeuntially that have different combination of options specified by customers. In just in time (JIT) environment, production smoothing becomes an important issue for sub-lines which supply the necessary parts to each workstation of the assembly line. Another important issue is to avoid line stopping caused by work overload in workstations. To find a sequence which minimizes the costs associated with line stoppage and the option parts inventory level, a nonlinear mixed integer programming is formulated. Recognizing the limit of the Branch and Bound technique in large sized problems, a heuristic solution procedure is proposed. The performance of the heuristic is compared with the Branch and Bound technique through randomly generated test problems. The computational results indicate that on the average the heuristic solutions deviate approximately 3.6% from the optimal solutions.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.117-133
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• 2011

In this paper, we present a frequency reassignment problem (FRP) arising from the reconfiguration of radio networks such as adding new base stations (BSs) and changing the number of frequencies assigned to BSs. For this problem, we develop an integer programming (IP) model that minimizes the sum of frequency reassignment cost and the cost for unsatisfied frequency demands, while avoiding interference among frequencies. To obtain tight lower bounds, we develop some valid inequalities and devise an objective function relaxation scheme. Also, we develop a simple but efficient heuristic procedure to solve large size problems. Computational results show that the developed valid inequalities are effective for improving lower bounds. Also, the proposed tabu search heuristic finds tight upper bounds with average optimality gap of 2.3%.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.178-194
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• 2010

To improve the ship operation in automated container terminals, it is important to schedule different types of handling equipment to operate synchronously. For example, a vehicle with container receiving and lifting capabilities is used to transport containers from a storage yard to a vessel and vice versa, while a triple quay crane (QC) can handle up to three 40-ft containers simultaneously. This paper discusses the manner in which vehicles should be assigned to containers to support such multi-lifts of QCs by using information about the locations and times of deliveries. A mixed-integer programming model is introduced to optimally assign delivery tasks to vehicles. This model considers the constraint imposed by the limited buffer space under each QC. A procedure for converting buffer-space constraints into time window constraints and a heuristic algorithmfor overcoming the excessive computational time required for solving the mathematical model are suggested. A numerical experiment is conducted to compare the objective values and computational times of the heuristic algorithm with those of the optimizing method to evaluate the performance of the heuristic algorithm.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.151-166
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• 1994

The manufacturing environment on which this research is focused is an FMS in which AGVs are used for material handling and each part type has one or more process plans. The research aims at developing a methodology whereby, given a part and volume mix for production during any production session, the best set of process plans including one plan per part type is selected and the best unidirectional AGV guidepath can be dynamically reconfigured in response to changes in parts and lot sizes combination. For the integrated PPS/FGD problem in which two functions of process plan selection (PPS) and flexible AGV guidepath design (FGD) are integrated, a zero-one integer programming model is developed. The integrated problem is decomposed into two subproblems, process plan selection given a directed AGV layout and AGV guidepath design with a fixed process plan per part type. A heuristic algorithm that alternately and iteratively solves these two subproblems is developed. The effectiveness of the heuristic algorithm is tested by solving various randomly generated sample problems and comparing the heuristic solutions with those obtained by an exact procedure. From the test results, the following conclusions are drawn: 1) For a reasonable size problem, the heuristic is very effective. 2) By integrating the two functions of PPS and FGD, a remarkable benefit in total production time for a given part and volume mix is gained.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.8-17
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• 2005

This paper dealt with a kind of heterogeneous vehicle routing problem with known demand and time deadline of customers. The customers are supposed to have one of tight deadline and loose deadline. The demand of customers with tight deadline must be fulfilled in the deadline. However, the late delivery is allowed to customers with loose deadline. That is, the paper suggests a model to minimize total acquisition cost, total travel distance and total violation time for a fleet size and mix vehicle routing problem with time deadline, and proposes a heuristic algorithm for the model. The proposed algorithm consists of two phases, i.e. generation of an initial solution and improvement of the current solution. An initial solution is generated based on a modified insertion heuristic and iterative Improvement procedure is accomplished using neighborhood generation methods such as swap and reallocation. The proposed algorithm is evaluated using a well known numerical example.