• Journal of the Society of Naval Architects of Korea
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• v.54 no.1
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• pp.57-62
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• 2017

These days, shipbuilding companies are making an effort to adopt the IT technology in order to improve the production efficiency. One such effort is to utilize a planning and scheduling system to predict the production cost in advance. In this system, assessing the welding material quantity is an important factor. Unfortunately, obtaining the welding material quantity in the early design stage is extremely difficult because the detailed production information, which is essential in deriving the cost associated with welding, is normally available at a later stage. This paper aims at developing a computerized program that produces an index to estimate the welding material quantity in the early design stage. By using only three-dimensional geometric information, the program analyzes the production process and estimates the welding material quantity at any design or production stage when no production information is available. The results can be used for the planning and scheduling system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.299-299
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• 1995

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.262-275
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• 2012

This paper develops a multistage scheduling algorithm for the module operation of the LCD(Liquid Crystal Display) production systems and tests the efficiency of the proposed algorithm. The module operation is a multistage form composed of multiple sub operations of processes, and each stage is consists of multiple lines with the same kinds of machines. This paper presents a mathematical modeling reflecting the constraints of the LCD module operation and develops a multistage scheduling algorithm based on tabu search metaheuristic approach. For this purpose, an production order is assigned to a line of the sub operations and a sequence of the assigned order is rearranged to draw an efficient schedule. Simulation experiments test performance measures and show the efficiency of the proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.75-85
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• 1985

The application of GT results in the mass production effect to multi-product, small lot-sized production. Group scheduling, which is operations scheduling based on the GT concept, is analyzed in a multistage manufacturing system. But the research has been limited in independent setup time models. A heuristic algorithm has been developed to minimize the mean flow time when setup times are dependent to sequence of group in multistage. For evaluation of the heuristic algorithm, the solution of heuristic algorithm is compared with that of random scheduling. The result of comparison indicates that the proposed heuristic algorithm provides good solutions with relatively fewer computational effort.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.207-211
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• 2021

This paper addresses a two-stage flexible flow shop scheduling problem in which there is one machine in stage 1 and two identical machines in stage 2. The objective is the minimization of the total completion time. The problem is formulated by a mixed integer quadratic programming (MIQP) and a hybrid simulated annealing (HSA) is proposed to solve the MIQP. The HSA adopts the exploration capabilities of a genetic algorithm and incorporates a simulated annealing to reduce the premature convergence. Extensive computational tests on randomly generated problems are carried out to evaluate the performance of the HSA.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.179-193
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• 1995

A multi-objective, single-stage scheduling problem with stochastic processing times is considered where the objective is to simultaneously minimize the expected value and the variance of total flowtime, and the mean probability of tardiness. In cases where processing times follow normal distributions, a method using pairwise interchange of two jobs(PITJ) is proposed to generate a set of the approximate efficient schedules. The efficient schedules are not dominated by the criterion vectors of any other permutation schdules in the feasible region. Numerical experiments performed to ascertain the effectiveness of PITJ algorithm are also reported in the results.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.801-803
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• 2005

Fundamentally, success of the competitive electricity market is dependent on efficient market design. However, since electricity incorporates various physical constraints as other commodities, the resource assignment (i.e., dispatch scheduling) is also one of requisites for the successful operation of electricity market. Therefore, efficient dispatch scheduling is an important issue to succeed in the deregulated electricity market and the efficiency of this electricity market may be considerably increased by systematic studies on dispatch scheduling algorithm and corresponding constraints, especially system security. Moreover, contrary to traditional vertically-integrated electric power industry condition, since various decision-makings in deregulated electricity market are directly connected with market participants' benefits, only rational dispatch scheduling algorithm can convince these participants. Therefore, it can provide a basis of grievance prevention. In this paper, we propose an algorithm for security constrained dispatch scheduling with respect to load curtailment. Proposed algorithm decomposes the dispatch problem into a master problem corresponding to basecase optimal power flow (OPF) and several subproblems corresponding a series of contingencies using two-stage optimization technique.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.831-840
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• 1992

This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

• IE interfaces
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• v.13 no.2
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• pp.225-233
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• 2000

In this paper, we develope a genetic algorithm for the erection scheduling in shipbuilding. Erection, the final manufacturing stage of shipbuilding, involves the landing and joining of blocks at drydock. Since several ships are built simultaneously at the same drydock and they compete with the common constrained production resource such as labor, space, and crane, we should consider both ship-specifics and common resource constraints for the desirable erection scheduling. Ship erection should also satisfy the predetermined dock cycle given from higher level production planning. Thus, erection schedule of a ship can be represented as a PERT/CPM project network with its own deadline. Since production resources are shared, the erection scheduling become the so-called multi-project scheduling problem with limited resources, which can not be solved easily due to the large size of project network. We propose a function as a minimization of load index which represented the load deviation over time horizon considering the yard production strategy. For the optical parameter setting, we tried various experiments. We verified that the proposed approach was effective to deal with the erection scheduling problem in shipbuilding.