• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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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.

• 한국경영과학회지
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• 제35권3호
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• pp.25-43
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• 2010

We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.

• 대한산업공학회지
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• 제27권3호
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• pp.315-327
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• 2001

This paper considers the problem of operation sequencing in nonlinear process planning, which is the problem of selecting and sequencing operations required to produce a part with the objective of minimizing the sum of operation processing costs and machine, setup and tool change costs. Main constraints are the precedence relations among operations. The problem can be decomposed into two subproblems: operation selection and operation sequencing. We suggest four simulated annealing algorithms, which solve the two subproblems iteratively until a good solution is obtained. Here, the operation selection problem can be solved using a shortest path algorithm. Application of the algorithms is illustrated using an example. Also, to show the performances of the suggested algorithms, computational experiments were done on randomly generated test problems and the results are reported. In particular, one of the suggested algorithms outperforms an existing simulated annealing algorithm.

• 한국정보시스템학회지:정보시스템연구
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• 제25권1호
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• pp.159-182
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• 2016

Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.

• 산업경영시스템학회지
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• 제36권3호
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• pp.95-108
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• 2013

The problem of constrained sequencing of a set of jobs on a conveyor system with the objective of minimizing setup cost is investigated in this paper. A setup cost is associated with extra material, labor, or energy required due to the change of attributes in consecutive jobs at processing stations. A finite set of attributes is considered in this research. Sequencing is constrained by the availability of conveyor junctions. The problem is motivated by the paint purge reduction problem at a major U.S. automotive manufacturer. We first model a diverging junction with a sequence-independent setup cost and predefined attributes as an assignment problem and this model is then extended for a more general situation by relaxing the initial assumptions in various ways.

• 대한산업공학회지
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• 제12권1호
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• pp.81-94
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• 1986

A shortest path dynamic programming formulation is proposed and attemped to solve an uncapacitated expansion sequencing problem. It is also compared with the Extended Binary State Space approach with total capacity. Difficulties and merits associated with the formulation are discussed. The shortest path dynamic programming lacks the separability condition and an optimal solution is not guaranteed. However it has other merits and seems to be the practical solution procedure for the expansion sequencing problem in a sense that it finds near optimal solution with less state evaluations.

• 한국경영과학회지
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• 제26권4호
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• pp.109-124
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• 2001

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed model assembly lines (MMALs). Line balancing and model sequencing are important for an efficient use of MMALs. The two problems of balancing and sequencing MMALs are tightly related with each other. However, In almost all the existing researches on mixed-model production lines, the two problems have been considered separately. In this research, an endosymbiotic evolutionary a1gorithm, which is a kind of coevolutionary a1gorithm, is adopted as a methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary a1gorithm to solving the integrated problem. Some evolutionary schemes are used In the a1gorithm to promote population diversity and search efficiency. The proposed a1gorithm is compared with the existing evolutionary algorithms in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

• Management Science and Financial Engineering
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• 제5권2호
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• pp.55-59
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• 1999

In this note, we introduce the Fire Sequencing Problem, which arises in military operations. Given m weapons, n fixed targets nad required duration of firing of the weapons on the targets, we want to determine the start time of firing on each target so that makespan is miniized while satisfying various operational constraints. We show that the decision problem of the Fire Sequencing problem is strongly NP-complete and remains strongly NP-complete even if the number of weapons is two. We also briefly discuss the results with respect to the complexities of several well-known scheduling models.

• 대한산업공학회지
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• 제11권2호
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• pp.141-154
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• 1985

The capacity expansion problem has been defined. Existing literatures on capacity expansion problems have been reviewed and unified under a structure of problem domain. The problem domain has been defined by three relavent coordinates; function or objective of the project, consideration of resource allocation, and consideration of project sequencing. Long range planning is of vital importance in setting up ultimately efficient capital investment plans to meet immediate demand increase. Simplified expansion sequencing example problems have been introduced and solved to help understanding of a solution scheme.

• 한국항해항만학회지
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• 제29권2호
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• pp.141-146
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• 2005

For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.