• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.35-49
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• 1993

The node coloring problem is a problem to color the nodes of a graph using the minimum number of colors possible so that any two adjacent nodes are colored differently. This problem, along with the edge coloring problem, has a variety of practical applications particularly in item loading, resource allocation, exam timetabling, and channel assignment. The node coloring problem is an NP-hard problem, and thus many researchers develop a number of heuristic algorithms. In this paper, we survey and classify those heuristics with the emphasis on how an algorithm orders the nodes and colors the nodes using a determined ordering.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1117-1122
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• 1993

The environment for surface mounting machines plays an important role in a throughput. An approach to organize the optimal integrated environment for surface mounting machines is presented to increase a throughput. An optimization problem is divided into a feeder setting problem and a task sequencing problem. Two algorithms for each problem are proposed. The feeder setting problems is optimized by an algorithm based on heuristic methods. The task sequencing problem is modeled as a TSP(Traveling salesman problem). An algorithm based on a heuristic tour-to-tour improvement method for TSP is proposed to optimize the task sequencing problem. A simulation is carried out to test developed algorithms.

• Steel and Composite Structures
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• v.8 no.6
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• pp.475-490
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• 2008

A hybrid tabu-simulated annealing algorithm is proposed for the optimum design of steel frames. The special character of the hybrid algorithm is that it exploits both tabu search and simulated annealing algorithms simultaneously to obtain near optimum. The objective of optimum design problem is to minimize the weight of steel frames under the actual design constraints of AISC-LRFD specification. The performance and reliability of the hybrid algorithm were compared with other algorithms such as tabu search, simulated annealing and genetic algorithm using benchmark examples. The comparisons showed that the hybrid algorithm results in lighter structures for the presented examples.

• Korean Management Science Review
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• v.33 no.2
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• pp.1-10
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• 2016

We treats a job scheduling in a 2-machine flow-shop problem with outsourcing strategy allowed. Jobs in the first machine are processed in-house or outsourced to the other companies. In this paper, all the considered jobs are determined to be in-house processed or outsourced. When a job is outsourced, then the firm should pay an outsourcing cost additionally. We want to minimize the sum of the outsourcing costs and the total completion times of finished jobs. In this paper, some solution properties are characterized, and then some heuristic algorithms and a branch-and-bound solution algorithm are derived. This paper evaluates finally the performance of the proposed algorithms during the numerical tests.

• 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 Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.63-71
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• 2003

This paper analyses a deterministic scheduling problem concerned with manufacturing multiple types of components at a pre-assembly stage composed of parallel fabrication machines. Each component part is machined on a fabrication machine specified in advance. The manufactured components are subsequently assembled into products. The completion time of a job(product) is measured by the latest completion time of its all components at the pre-assembly stage. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs. Two lower bounds are derived and tested in a branch-and-bound scheme. Also, three constructive heuristic algorithms are developed based on the machine aggregation and greedy strategies. Some empirical evaluation of the performance of the proposed branch-and-bound and heuristic algorithms are also performed.

• Structural Engineering and Mechanics
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• v.42 no.6
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• pp.783-797
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• 2012

A new hybrid meta-heuristic optimization algorithm is presented for design of structures. The algorithm is based on the concepts of the charged system search (CSS) and the particle swarm optimization (PSO) algorithms. The CSS is inspired by the Coulomb and Gauss's laws of electrostatics in physics, the governing laws of motion from the Newtonian mechanics, and the PSO is based on the swarm intelligence and utilizes the information of the best fitness historically achieved by the particles (local best) and by the best among all the particles (global best). In the new hybrid algorithm, each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Three different types of structures are optimized as the numerical examples with the new algorithm. Comparison of the results of the hybrid algorithm with those of other meta-heuristic algorithms proves the robustness of the new algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.7-12
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• 1985

Line balancing algorithm can be classified by two class, the analytical method and the heuristic method. In this thesis the study was focused on the determinstic line balancing model of the single model production assembly line balancing which is one of the heuristic method. The algorithm of Tonge, Kilbridge & Wester, Helgeson & Birnie which is using the analytical method was examined with one example. And then the algorithms were compared with using line balancing-efficiency, number of work station, standard deviation and range. The result showed that Helgeson & Birnie algorithm is the most convenient in use. A computer program was run in order to use Helgeson & algorithm more conveniently.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.90-99
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• 2003

Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.