• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.113-121
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• 2014

This paper considers a scheduling problem in a two-machine flowshop with outsourcing strategy incorporated. The jobs can be either processed in the first machine or outsourced to outside subcontractors. This paper wants to determine which jobs to be processed in-house and which jobs to be outsourced. If any job is decided to be outsourced, then an additional outsourcing cost is charged The objective of this paper is to minimize the sum of scheduling cost and outsourcing cost under a budget constraint. At first this paper characterizes some solution properties, and then it derives solution procedure including DP (Dynamic Programming) and B&B (Branch-and-Bound) algorithms and a greedy-type heuristic. Finally the performance of the algorithms are evaluated with some numerical tests.

• Advances in Computational Design
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• v.5 no.3
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• pp.209-231
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• 2020

In order to evaluate the performance of three heuristic optimization algorithms, namely, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO) for optimal stacking sequence of laminated composite plates with respect to critical buckling load and non-dimensional natural frequencies, a multi-objective optimization procedure is developed using the weighted summation method. Classical lamination theory and first order shear deformation theory are employed for critical buckling load and natural frequency computations respectively. The analytical critical buckling load and finite element calculation schemes for natural frequencies are validated through the results obtained from literature. The comparative study takes into consideration solution and computational time parameters of the three algorithms in the statistical evaluation scheme. The results indicate that particle swarm optimization (PSO) considerably outperforms the remaining two methods for the special problem considered in the study.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.155-164
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• 1996

Biomass to methane via anaerobic digestion conversion is a good supply method of substitutable energy resources. The economic viability of this technology is contingent upon managing the production facilities in a cost effective manner. The problem is to determine the batch production sequence as well as the batch residence times in the digester so as to maximize total gas production over a given planning horizon. The problem is difficult to solve since the batch sequencing decisions and the batch residence time decisions cannot be isolated. This paper developes a heuristic algorithm which is based on a dynamic programming procedure for the multiple feedstock sequencing and scheduling biogas production systems and demonstrates to yield good results.

• Journal of the military operations research society of Korea
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• v.29 no.1
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• pp.112-119
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• 2003

The procedure and implementation of an simulation based production planning and scheduling system. Production planning and scheduling is important problem in manufacturing field. It is so important for delivery quality as well as productivity, too. In this paper, heuristic production planning and scheduling module for improving delivery quality and productivity will be discussed. Beginning with total demand and initial work in process, the algorithms for production scheduling and planning can efficiently generate a feasible production resources and capacity schedule results in high resource utilization, minimum number of the late orders and reduced labor variability. The algorithm is executed to achieve the best on time delivery performance. The developed heuristic algorithms in the module will be expected to provide the better delivery performance and productivity.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.55-71
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• 2006

We perform a computational study on 0-1 knapsack problems generated under explicit correlation induction. A total of 2000 100-variable test problems are solved. We use two solution methods: (1) a well known heuristic and (2) a representative branch and bound type algorithm. Two different performance measures are considered: (1) the number of nodes needed to find an optimal solution and (2) the relative error of the heuristic solution. We also examine the effect of different joint probability mass functions (pmfs) for the coefficient values on the performance of the solution procedure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.10
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• pp.675-682
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• 1988

An improved algorithm for optimal daily hydrothermal unit commitment is proposed in this paper. Especially, for the purpose of guarantee on the existence of feasible solution all the time, the secondary states as well as the primary state are considered at each step in the procedure of solution by Hybird Dynamic Programming to solve the problem of which solution may not exist due to the increased number of constraints to be taken into account. The computational problem which may be caused in the course of considering secondary policies through whole steps of the period examined is solved by the heuristic judgement in every step taking load variation rates into account. The effectivness of the algorithm has been demonstrated by applying it to a sample power system.

• Smart Structures and Systems
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• v.20 no.5
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• pp.607-618
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• 2017

In this research, a newly developed nature-inspired optimization method, the Lion Pride Optimization algorithm (LPOA), is utilized for optimal design of composite steel box girder bridges. A composite box girder bridge is one of the common types of bridges used for medium spans due to their economic, aesthetic, and structural benefits. The aim of the present optimization procedure is to provide a feasible set of design variables in order to minimize the weight of the steel trapezoidal box girders. The solution space is delimited by different types of design constraints specified by the American Association of State Highway and Transportation Officials. Additionally, the optimal solution obtained by LPOA is compared to the results of other well-established meta-heuristic algorithms, namely Gray Wolf Optimization (GWO), Ant Lion Optimizer (ALO) and the results of former researches. By this comparison the capability of the LPOA in optimal design of composite steel box girder bridges is demonstrated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.17
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• pp.39-46
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• 1988

This Paper is concerned with a man-multi machine assignment problem to minimize idle time. Assuming different types of semi-automatic machines with deterministic service-processing time, the problem approaches by sequential dependent one operator can handle several machines, where determine optimal range the cost of idle labor and machine time is to be minimized in preparing a work schedule. The Procedure, to establish man-machine assignment model, and it's results are: (1) Objective function to minimize opportunity loss cost, which is happened by idle time, is verified recursive process through heuristic method. (2) The algorithm, is programmed by BASIC language for personal computer, and a numerical example is given to illustrate the heuristic algorithm. This study will be helpful to enhance productivity of Shopflooras a result of increasing the efficiencies of both operator and machine.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.35-46
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• 1987

To minimize makespan for preemptive sequence dependent job scheduling with parallel identical processors, fundamental results, as the basis of new algorithm to be presented, such as McNauton's algorithm for independent jobs, Hu's characterization for dependent jobs, and Muntz-Coffman's algorithm, were first introduced. Then a huristic procedure was presented applying those concepts of zoning of assembly line balancing and of resource leveling on CPM network scheduling with two or more of parallel machines in general. New procedure has eliminated presumative machine assignment using ${\rho}$, rate of resource capability (${\rho}$ < 1), for practical scheduling.