• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.161-166
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• 1997

The blocks world is the primary problem domain in the artificial intelligence. Many planners have been developed in domain-independent. Gupta de fined the deadlock in the blocks world, and he proved that decision making in t he blocks world is NP-Complete problem. In this paper the properties of the dea dlock are analyzed, and a heuristic algorithms which can handle the deadlock of the Gupta's nondeterministic algorithm is proposed.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.

• Management Science and Financial Engineering
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• v.5 no.2
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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.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.14-35
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• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.13-35
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• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Korean Management Science Review
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• v.29 no.2
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• pp.143-155
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• 2012

The purpose of this study is to formulate and solve the scheduling problem to heat-treatment process in forging process and apply it to industries. Heat-treatment is a common process in manufacturing heavy forged products in ship engines and wind power generators. Total complete time of the schedule depends on how to group parts and assign them into heat furnace. Efficient operation of heat-treatment process increases the productivity of whole production system while scheduling the parts into heat-treatment furnace is a combinatorial problem which is known as an NP-hard problem. So the scheduling, on manufacturing site, relies on engineers' experience. To improve heat-treatment process schedule, this study formulated it into an MIP mathematical model which minimizes total complete time. Three methods were applied to example problems and the results were compared to each other. In case of small problems, optimal solutions were easily found. In case of big problems, feasible solutions were found and that feasible solutions were very close to lower bound of the solutions. ILOG OPL Studio 5.5 was used in this study.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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• pp.35-49
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• 2008

To load a container in a yard block onto a ship, a Transfer Crane (TC) moves to a target yard bay, then its hoist picks up a selected container and loads it onto a waiting Yard Truck (YT). An optimal routing problem of Transfer Crane is a decision problem which determines a given TC's the visiting sequence of yard-bays and the number of containers to transfer from each yard-bay. The objective is to minimize the travel time of the TC between yard-bays and setup time for the TC in a visiting yard. In this paper, we shows that the problem is NP-complete, and suggests a new formulation for it. Using the new formulation for the problem, we investigate some characteristics of solutions, a lower and upper bounds for it. Moreover, our lower and upper bound is very efficient to applying some instances suggested in a previous work.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.146-158
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• 1991

In this paper, we deal with the TSP (Traveling Salesperson Problem) which is well-known as NP-complete optimization problem. the TSP is applicable to network routing. task allocation or scheduling. and VLSI wiring. Well known numerical methods such as Newton's Metheod. Gradient Method, Simplex Method can not be applicable to find Global Solution but the just give Local Minimum. Exhaustive search over all cyclic paths requires 1/2 (n-1) ! paths, so there is no computer to solve more than 15-cities. Heuristic algorithm. Simulated Annealing, Artificial Neural Net method can be used to get reasonable near-optimum with polynomial execution time on problem size. Therefore, we are able to select the fittest one according to the environment of problem domain. Three methods are simulated about symmetric TSP with 30 and 50-city samples and are compared by means of the quality of solution and the running time.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.81-88
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• 2016

The optimal solution of quadratic assignment problem (QAP) cannot get done in polynomial time. This problem is called by NP-complete problem. Therefore the meta-heuristic techniques are applied to this problem to get the approximated solution within polynomial time. This paper proposes an algorithm for a random type QAP, in which the instance of two nodes are arbitrary. The proposed algorithm employs what is coined as a max flow-min distance rule by which the maximum flow node is assigned to the minimum distance node. When applied to the random type QAP, the proposed algorithm has been found to obtain optimal solutions superior to those of the genetic algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.409-416
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• 2003

We consider the problem of grouping orders into lots. The problem is modelled by a graph G = (V, E). where each node $\nu\;\in\;V$ denotes order specification and its weight $\omega(\nu)$ the orders on hand for the specification. We ran construct a lot simply from orders or single specification For a set of nodes (specifications) $\theta\;\subseteq\;V$, if the distance or any two nodes in $\theta$ is at most d, it is also possible to make a lot using orders on the nodes. The objective is to maximize the number of lots with size exactly $\lambda$. In this paper, we prove that our problem is NP-Complete when d = 2, $\lambda\;=\;3$ and each weight is 0 or 1. Moreover, it is also shown to be NP-Complete when d = 1, $\lambda\;=\;3$ and each weight is 1, 2 or 3