• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.472-482
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• 2013

This paper proposes a wireless LAN topology configuration method for enhancing indoor location-awareness and improving network performance simultaneously. We first develop four objective functions that yield objective goals significant to the optimal design of a wireless LAN topology in terms of location-awareness accuracy and network performance factors. Then, we develop metaheuristic algorithms such as simulated annealing, tabu search, and genetic algorithm that examine the proposed objective functions and generate a near-optimal solution for a given objective function. Finally, four objective functions and metaheuristic algorithms developed in this paper are exploited to evaluate and measure the performance of the proposed wireless LAN topology configuration method.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.204-214
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• 2010

A manufacturing/remanufacturing system is investigated with the consideration of required minimum quality of end-of-used products. A constant demand is satisfied by remanufacturing end-of-used products and manufacturing raw materials outsourced from outside. It is assumed in this system that the buyback price and remanufacturing cost are related to the different quality level of end-of-used products. For remanufacturing, only the used products that satisfy a required minimum quality level will be recycled. Thus, the returning rate is a function of the required minimum quality level. Functions of returning rate, buyback price and remanufacturing cost, which are closely connected to the quality level of end-of-used products, are investigated here. Treating the required minimum quality level of end-of-used products, the length of a cycle, the number of manufacturing lots and remanufacturing lots in a cycle as decision variables, the mathematical models with the objective of minimizing the average total cost are constructed. Through construction of a solution process based on Tabu Search algorithm and calculating examples, the validity of the models is illustrated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.167-168
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• 2009

As the rapid increase of the container trade, most of the container terminals strive to improve the container handling productivity. Therefore, they consider to find efficient operating strategies and to introduce new container handling facilities. In terms of equipment, there are a variety of types of quay cranes. Single-lift crane operates only one container regardless of size and twin-lift crane operates two 20' containers or one 40' container simultaneously. Tandem crane, recently introduced, can operate four 20' containers or two 40' containers simultaneously. In this paper, we propose the mathematical model and the solution procedure of the ship loading scheduling problem for the tandem crane.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.41-41
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• 1992

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 Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.35-41
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• 2002

To solve the large scale optimization problem approximately, various approaches have been introduced. They are mainly based on recent research advancement of simulations for evolutions, flocking, annealing, and interactions among organisms on artificial environments. The typical ones are simulated annealing(SA), artificial neural network(ANN), genetic algorithms(GA), tabu search(TS), etc. Recently the particle swarm optimization(PSO) has been introduced. The PSO simulates the process of birds flocking or fish schooling for food, as with the information of each agent Is share by other agents. The PSO technique has been applied to various optimization problems of which variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process particle swarm optimization(PSO) algorithm. The proposed tool is effective for understanding the searching process of PSO method and educational for students.