• Journal of Communications and Networks
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• v.7 no.4
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• pp.471-477
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• 2005

This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.555-562
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• 2009

At container terminals, a major measurement of productivity can be work-efficiency in quay-side. At the apron, containers are loaded onto the ship and unloaded to apron by Q/C(Quay Crane). For improving the productivity of quay crane, the more efficient Y/T(Yard Tractor) operation method is necessary in container terminals. Between quay-side and yard area, current transferring methods is single-cycling which doesn't start loading unless it finishes unloading. Dual-cycling is a technique that can be used to improve the productivity of quay-side and utility of yard tractor by ship loading and unloading simultaneously. Using the dual-cycling at terminals only necessitates an operational change without purchasing extra equipment. Exactly, Y/T operation method has to be changed the dedicate system to pooling system. This paper presents an efficient ship loading and unloading plan in container terminals, which use the dual-cycling. We propose genetic and tabu search algorithm for this problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.163-168
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• 2005

It is one of the most important things to determinate optimized cutting conditions which satisfy productivity and cost simultaneously in production and CAPP systems. These days many researchers have figured out the optimizing way for solutions of multi-object function to find the approach methods using algorithm such as genetic algorithm or tabu search, etc., instead of mathematical methods. The main creation of objective function is proposed by empirical method but which is difficult to set it up and to analysis. In this paper, an optimization method of cutting condition is shown using the ANN and GA for the multi-objective function in high speed machining.

• IE interfaces
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• v.21 no.3
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• pp.254-261
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• 2008

Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.570-576
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• 2004

It is very difficult to efficiently solve a large-scaled maximal covering problem(MCP) by a genetic algorithm. In this paper, we present new crossover and mutation operators specially designed for genetic algorithms to solve large-scaled MCPs efficiently. We also introduce a novel genetic algorithm employing unexpressed genes. Unexpressed genes are the genes which are not expressed and thus do not affect the evaluation of the individuals. These genes play the role of reserving information susceptible to be lost by the application of genetic operations but is suspected to be potentially useful in later generations. The genetic algorithm employing unexpressed genes enjoys the advantage of being able to maintain diversity of the population and thus can search more efficiently to solve large-scaled MCPs. Experiments with large-scaled real MCP data has shown that our genetic algorithm employing unexpressed genes significantly outperforms tabu search which is one of the popularly used local neighborhood search algorithms for optimization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.459-463
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• 2007

Overlay multicast is an emerging technology for next generation Internet service to various groups of multicast members. It will take the place of traditional IP multicast which is not widely deployed due to the complex nature of its technology. The overlay multicast which effectively reduces processing at IP routers can be easily deployed on top of a densely connected IP network. An end-to-end delay problem is considered which is serious in the multicast service. To periodically optimize the route in the overlay network and to minimize the maximum end-to-end delay, overlay multicast tree is investigated with genetic Algorithm. Outstanding experimental results are obtained which is comparable to the optimal solution and the tabu search.

• Korean Management Science Review
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• v.17 no.1
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• pp.41-54
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• 2000

in the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.17-28
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• 1998

This study suggests a procedure for designing cellular manufacturing systems (CMS) which are combined with automated guided vehicles (AGVs) using a tandem configuration. So far most of the previous studies have dealt with conventional design problems not considering the layout and the characteristics of transporters used in CMS. A mathematical model is developed using the service time to perform material transfers as a suitable meassure. The service capacity of AGVs and space limitations are also reflected in this model. As the model can be shown strongly NP-hard, a heuristic algorithm is presented, in which each cell is temporarily formed using both the set covering model and similarity coefficients, and then locations of the cells are determined by means of tabu search and finally machine perturbations are carried out. An example problem is solved to demonstrate the algorithm developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.693-696
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• 2006

Global optimization is a method for finding more reliable models in various fields, such as financial engineering, pattern recognition, process optimization. In this study, we compare and analyze the performance of the state-of-the-art global optimization techniques, which include Genetic Algorithm (DE,SCGA), Simulated Annealing (ASA, DSSA, SAHPS), Tabu & Direct Search (DTS, DIRECT), Deterministic (MCS, SNOBIT), and Trust-Region algorithm. The test functions for the experiments are Benchmark problems in Hedar & Fukushima (2004), which are evaluated with respect to efficiency and accuracy. Through the experiment, we analyse the computational complexity of the methods and finally discuss the pros and cons of them.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.179-186
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• 2006

There was a lot of research to integration of the transshipment and inventory problem in supply chain. Such a integration of inventory and transshipment problem called IRP (Inventory Routing Problem). We consider a distribution problem in which a set of products has to be shipped from a supplier to several retailers in a given planning horizon. Transshipment from the supplier to the retailer is performed by vehicles of limited capacity. Each retailer determines replenishment leadtime and order quantity with buffer management. A supplier determines optimal vehicle routing in supply chain. We suggest a heuristic algorithm which be used TOC buffer management in a replenishment problem and a tabu search algorithm in VRP (Vehicle Routing Problem).