• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.133-141
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• 2001

Rapid development in computer and network technology these days has created in environment in which decisions for manufacturing companies can be made in a much broader perspective. Especially, better decisions on production and distribution planning(PDP) problems can be made laking advantage of real time information from all the parties concerned. However, since the PDP problem-a core part of the supply chain management- is known to be the so-called NP-hard problem, so heuristic methods are dominantly used to find out solutions in a reasonable time. As one of those heuristic techniques, many previous studios considered genetic a1gorithms. A standard genetic a1gorithm applies rules of reproduction, gene crossover, and mutation to the pseudo-organisms so the organisms can pass along beneficial and survival-enhancing trails to a new generation. When it comes to representing a chromosome on the problem, it is hard to guarantee an evolution of solutions through classic a1gorithm operations alone, for there exists a strong epitasis among genes. To resolve this problem, we propose a hybrid genetic a1gorithm based on Silver-Meal heuristic. Using IMS-TB(Intelligent Manufacturing System Test-bed) problem sets. the good performance of the proposed a1gorithm is demonstrated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.34-39
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• 2008

Nash Equilibrium(NE) is essential to investigate a participant's bidding strategy in a competitive electricity market. Congestion on a transmission line makes it difficult to compute the NE due to causing a mixed strategy. In order to compute the NE of a multi-player game, some heuristics are proposed with concepts of a key player and power transfer distribution factor in other studies. However, generation capacity constraints are not considered and make it more difficult to compute the NE in the heuristics approach. This paper addresses an effect of generation capacity limits on the NE, and suggest a solution technique for the mixed strategy NE including generation capacity constraints as two heuristic rules. It is reported in this paper that a role of the key player who controls congestion in a NE can be transferred to other player depending on the generation capacity of the key player. The suggested heuristic rules are verified to compute the mixed strategy NE with a consideration of generation capacity constraints, and the effect of the generation constraints on the mixed strategy NE is analyzed in simulations of IEEE 30 bus systems.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.119-135
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• 1995

We consider problems of tool loading and scheduling in a flexible manufacturing system (FMS) in which tool transportation constitutes the major portion of material flows. In this type of FMSs, parts are initially assigned to machines and released to the machines according to input sequencing rules. Operations for the parts released to the machines are performed by tools initially loaded onto the machines or provided by an automatic tool transport robot when needed. For an efficient operation of such systems, therefore, we may have to consider loading and scheduling problems for tools in addition to those for parts. In this paper, we consider three problems, part loading, tool loading, and tool scheduling problems with the overall objective of minimizing the makespan. The part loading problem is solved by a method similar to that for the bin packing problem and then a heuristic based on the frequency of tool usage is applied for tool loading. Also suggested are part input sequencing and tool scheduling rules. To show the effectiveness of the overall algorithm suggested here, we compare it with an existing algorithm through a series of computational tests on randomly generated test problems.

• Korean Management Science Review
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• v.10 no.1
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• pp.171-192
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• 1993

In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule is presented. The MDR dispatching rule has been designed to maximize utilization of resources in a resource-constrained job shop with general precedence constraints. In shown that solving the above scheduling problem with the MDR dispatching rule is equivalent to multiple solving of the maximum clique problem. A graph theoretic approach is used to model the latter problem. The pairwise counting heuristic of computational time complexity O(n$^{2}$) is developed to solve the maximum clique problem. An attempt is made to combine the MDR dispatching rule with the existing look-ahead dispatching rules. Computational experience indicates that the combined MDR dispatching rules provide solutions of better quality and consistency than the dispatching rules tested in a resource-constrained job shop.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1108-1120
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• 1990

The present study is to develop an intelligent control system for flexible manufacturing system, which is suitable for a variety of manufacturing types with smaller production rates. The controller is designed to integrate heuristic rules with optimization techniques for loading as well as flow rate of parts and ultimately meeting performance indices. The control function implemented by an optimization technique is to calculate short term production rates of parts. The heuristic control determined by production rules requires knowledge base to evaluate selected loading alternatives according to short term production rate and current process information, and also to determine final decision pertaining to loading. In this case, the knowledge base is constructed using the rules for evaluating alternatives, decision criteria, and flow control of parts in manufacturing system. The database is formulated by means of managing and updating current process information. A graphic system to monitor current status of the function and operation of manufacturing system is developed, and computer simulation is carried out to evaluate the performance of the proposed controller.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.175-181
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• 2014

This paper suggests O(m) polynomial time heuristic algorithm to obtain the solution for the driver scheduling problem, DSP, that has been classified as NP-complete problem. The proposed algorithm gets the initial assignment of n minimum number of drivers from given m schedules. Nextly, this algorithm gets the minimum total time (TC) using 5 rules of swap and insert for decrease of over times (OT) and idle times (IT). Although this algorithm is a heuristic polynomial time algorithm with O(m) time complexity rules to be find a optimal (or approximate) solution, this algorithm is equal to metaheuristic methods for the 5 experimental data. To conclude, this paper shows the DSP is not NP-complete problem but Polynomial time (P)-problem with polynomial time rules.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.123-128
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• 2002

A fuzzy traffic controller with the control rules and the membership functions generated by using genetic algorithm is presented for crossroad management. Conventional fuzzy traffic controllers use control rules and membership functions generated by human operators. However, this approach does not guarantee the optimal solution to design fuzzy control system. Genetic algorithm is a good solution for an optimal problem requiring domain-specific knowledge that is often heuristic. In this paper, we use genetic algorithms to automatically determine the near optimal rules and their membership functions of fuzzy traffic controllers. The effectiveness of our method was shown through simulation of crossroad network.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.65-77
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• 1994

There are so many situations in which production schedules need to be rescheduled, due to the uncertainty or dynamic characteristics existing in manufacturing environment. Under the circumstances, it is necessary to build a system which helps a schedule manager understand the dynamic situations and reflect his insight into the system easily. We developed a system that can improve a production schedule. The system consists of a schedule editor and a schedule generator. The schedule editor, a rule-based system, always keeps a schedule feasible by keeping track of local changes in the revised one. The schedule generator consists of a two-phase heuristic method. In the lst phase it generates a schedule by a priority rule with Giffler and Thompson algorithm then it improves the performance in terms of the makespan in the 2nd phase. Experimental results show that, most of the times, the system generates a better schedule than the one with ordinary priority rules only.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.491-497
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• 2007

The planning and scheduling is considered as an important function because it influence to the overall performance of production in manufacturing system for supporting global objectives. In this paper, propose the hybrid approach to solve the problem which considered alternative resources and sequences, a sequence-dependent setups and transportation times. The objective of this problem is minimize the makespan with AGV traveling time. A iterative two heuristic algorithm(PSO, SA) is proposed to obtain the sequence of operations and CPLEX package is used to obtain the optimal sub-lot sizes(OLS) when the sequence of operations and greedy-based AGV dispatching rules are fixed or given. we show that performance of iterative two heuristic algorithms and simple numerical experiment.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.350-353
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• 1991

This study develops an expert system which solves the problems of the MTr/feeder overloads and the feeder constraints in automated radial distribution systems. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches which eliminates the system violation, while achieving the load balance of the MTrs/feeders. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in AI language Prolog. This system adopts the best-first tree search technique. The computational results are also prepared to show the performance of the heuristic algorithm developed.