• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.439-442
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• 2003

In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5％ decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.768-772
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• 2005

TSP(Traveling Salesman Problem) has been a nagging NP-complete problem to test almost every algorithmic idea in combinatorial optimization in vain. The main bottleneck is how to get the integer results {0,1} and to avoid sub-tours. We suggest simple and practical method in two steps. Firstly for every node, an initial Hamiltonian cycle us produced on the nearest neighbour concept. The node with nearest distance is to be inserted to form a increased feasible cycle. Secondly we improve the initial solution by exchanging 2 cuts of the grand tours. We got practical results within 1 from the optimum in 30 minutes for up to 200 nodes problems. TSP of real world type might be tackled practically in our formulation.

• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1349-1354
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• 2001

In the Traveling Salesman Problem(TSP), a set of N cities is given and the problem is to find the shortest route connecting them all, with no city visited twice and return to the city at which it started. Since TSP is a well-known combinatorial optimization problem and belongs to the class of NP-complete problems, various techniques are required for finding optimum or near optimum solution to the TSP. Especially DNA computing, which uses real bio-molecules to perform computations supported by molecular biology, has been studied by many researchers to solve NP-complete problem using massive parallelism of DNA computing. Though very promising, DNA computing technology of today is inefficiency because the effective computing models and operations reflected the characteristics of bio-molecules have not been developed yet. In this paper, I design new Polymerase Chain Reaction(PCR) operations of DNA computing to solve TSP.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.2 s.150
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• pp.245-254
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• 2006

The purposes of this study were to identify the perceived difference of salesman's service and relationship benefit according to types of customers, to explain the effects of salesman's service and relationship benefit on buying satisfaction and repurchase intention, and to reveal the influences of satisfaction with purchase on repurchase. The data were collected from 318 female adults in Gwangju using a questionnaire to salesmen's service, relationship benefits, buying satisfaction, repurchase intention, and were analysed with factor analysis, t-test and regressive analysis with SPSS 10.0. The results of this study were as follows: 1. The regular customers perceived a significantly higher salesmen's services and relationship benefits than irregular customers. 2. In regular customers, 'knowledge of products', 'etiquette' and 'confident benefits' had a significant influence on buying satisfaction. 'Confident benefits' had a significant influence on repurchase intention. Tn irregular customers, 'etiquette', 'easiness' and 'confident benefits' had a significant influence on satisfaction with purchase. 'Knowledge of products', 'easiness' and 'confident benefits' had a significant influence on repurchase intention. 3. Satisfaction with purchase had a significant influence on repurchase intention in both regular/irregular customers.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.315-322
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• 2006

Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.

• Journal of Fashion Business
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• v.16 no.4
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• pp.75-87
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• 2012

This study was to investigate the conversion intent of fashion store among college undergraduates. The conversion intent in internet shopping mall and local store was associated with store attributes and relationship quality. A random sample of undergraduate students completed a questionnaire that contained measure of Store attributes, Relationship quality, Conversion intent of fashion store. The results revealed that store attributes of local store were store comport/salesman service, product diversity, store location, price and the store attributes of internet shopping mall were product diversity/easy of navigation, store reliability, screen configuration, sales promotion. Also, the result founded that the conversion intent of fashion store is related to store comport/salesman service in local store and is related to product diversity/easy of navigation, screen configuration, promotion in internet shopping mall. Relationship quality is highly effected of the conversion intent of local store and internet shopping mall. We expect that this research results can be used as a basic material for another study and setting up the marketing strategies in fashion store.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.79-84
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• 2016

In this paper we consider the problem of finding the triplet (S,${\pi}$,f), where $S{\subseteq}V$, ${\pi}$ is a sequence of nodes in S and $f:V{\backslash}S{\rightarrow}S$ for a given complete graph G=(V,E). In particular, there exist two costs, $c^V_{uv}$ and $c^D_{uv}$ for $(u,v){\in}E$, and the cost of triplet (S,${\pi}$,f) is defined as $\sum_{i=1}^{{\mid}S{\mid}}c^V_{{\pi}(i){\pi}(i+1)}+2$ ${\sum_{u{\in}V{\backslash}S}c^D_{uf(u)}$. This problem is motivated by the integrated routing of the vehicle and drone for urban delivery services. Since a well-known NP-complete TSP (Traveling Salesman Problem) is a special case of our problem, we cannot expect to have any polynomial-time algorithm unless P=NP. Furthermore, for practical purposes, we may not rely on time-exhaustive enumeration method such as branch-and-bound and branch-and-cut. This paper suggests the simple heuristic which is motivated by the MST (minimum spanning tree)-based approximation algorithm and neighborhood search heuristic for TSP.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.237-242
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• 2003

Ant Colony System (ACS) Algorithm is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP). In this paper, we introduce ACS of new method that adds reinforcement value for each edge that visit to Local/Global updating rule. and the performance results under various conditions are conducted, and the comparision between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with tile original ACS in terms of solution quality and computation speed to these problem.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.3_4
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• pp.379-389
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• 2002

The purposes of this study were 1) to examine the conceptual structure of purchasing situations and affective states, 2) and to fine out the relationships among impulsive buying behavior, purchasing situations, and affective states in boutiques. The questionnaire was completed by 345 boutiques customers in Busan. Demographics showed that the customers were higher educated and had higher incomes than the average consumer in Busan. Data were analysed by factor analysis, and t-test. First, the purchasing situation perceived by boutiques customers consisted of five factors; Crowding, Atmosphere/service, Exhausting/salesman's attire, Display, and Price. The affective states related to the impulsive buying behavior in boutiques composed of three factors; Pleasant, Unpleasant, and Insecure. Second, the impulsive buyer perceived Exhausting/salesman's attire and the pleasant affection in stores higher than the unimpulsive buyer, and the unimpulsive buyer made higher scores than the impulsive buyer in the situation of C개wding, Atmophere/service, and the Unpleasant affection at boutiques. The results showed that impulsive buyer was influenced by purchasing situations and affective states in stores. They provided informations about impulsive buying useful to consumer behavior researchers and retailers related to boutiques.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.80-87
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• 2010

As express courier market expands rapidly, companies are exposed to fierce competition. To cope with struggle for their survival, they are continuously making efforts to improve their service system. Even if most of service centers are directly linked to a consolidation terminal in courier service network, some of them with regional disadvantages are operated in milk run type from/to the consolidation terminal, which is a traditional PDP (Pick-up and Delivery Problem). This study suggests an approach to solve the PDP with the objective of maximizing the incremental profit, which belongs to PTP (Profitable Tour Problem) class. After the PTP is converted to TSP (Traveling Salesman Problem) with the same objective, a heuristic algorithm based on GA (Genetic Algorithm) is developed and examined through an example problem in practice of a courier service company in Korea.