• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.157-164
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• 2023

This paper suggests O(n²) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(T_e) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate _minr_w(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate _minr_fi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.93-101
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• 2013

This paper suggests optimal location algorithm of new firm $A(F_A)^{\prime}s$ p(p$B(F_B)$ already operating q outlets of sports in the market. This algorithm selects top q nodes among $V=V{\backslash}F_B$ nodes that covers maximum nodes based on the shortest distance. Then, q nodes choose next node that has a maximum cover with inclusion-exclusion principle. At the time of same number of cardinality in q sets to pre-defined q, we select the maximum cover node set. This algorithm called by competitive algorithm. The competitive algorithm simply decides the optimal location of the outlets p=1,2,3,4 for q=5. Also, we show that the market share of competitive algorithm can be maximize.

• Spatial Information Research
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• v.18 no.3
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• pp.63-72
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• 2010

The vehicle routing problem with simultaneous pick-up and delivery (VRPSPD) is a variant of the vehicle routing problem (VRP) that customers require simultaneously a pick-up and delivery service. The main objective of VRPSPD is to minimize a cost of routes satisfying many constraints. Traditional VRPSPD have been dealt with a static environment. The static environment means that a routing data and plan cannot be changed. For example, it is difficult to change a vehicle's routing plan so that a vehicle serves the pick-up demands of new customers during the delivery service. Therefore, traditional approach is not suitable for dynamic environments. To solve this problem, we propose a novel approach for finding efficient routes using a real-time re-routing heuristics based on the Location Based Service (LBS). Our re-routing heuristics can generate a new route for vehicle that satisfies a new customer's demand considering the current geographic location of a vehicle. Experimental results show that our methodology can reduce the traveling cost of vehicles comparing with other previous methods.

• 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 Korea Society for Simulation
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• v.17 no.4
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• pp.133-142
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• 2008

AGV systems are widely used to increase the flexibility and the efficiency of the material handling systems. AGV systems are one of critical factors which determine the overall performance of the manufacturing systems. To this end, the optimal design for AGV systems is essential. Commercial simulation software is often used as an analysis tool during the design of AGV systems, however a series of procedures are desirable to simplify the analysis processes. In this paper, we present and develop the architecture for unidirectional AGV systems simulator which is able to consider approximate optimal unidirectional flow path and various operational parameters. The designed AGV systems simulator is based on JAVA, and it is developed to support designing approximate optimal unidirectional network by using Tabu search method. In addition, it enables users to design and evaluate AGV systems and to analyze alternative solutions easily. Simulation engine is consists of layout designer, AGV operation plan designer, and integrated AGVS layout designer. Users enter their system design/operation information into input window, then the entered information is automatically utilized for modeling and simulating AGV systems in simulation engine. By this series of procedures, users can get the feed back quickly.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.43-52
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• 2021

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1823-1840
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• 2023

In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.