An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

The purpose of this study was to empirically examine the effects of salespeople's self-determination, shared value; and communication satisfaction on their job satisfaction, organizational commitment, and turnover intention in a fashion company. Questionnaires were administered to 475 salespeople who worked in fashion shop at the time of the study. The data was analyzed via factor analysis, correlation analysis, and a structural equation model. The results indicated that self-determination was extracted as autonomy, competence, and relatedness. Only the relatedness of self-determination factors was positively correlated with formal and informal communication satisfaction. In addition, recognizing hared value was positively correlated with formal and informal communication satisfaction; whereas, the practice of shared value was positively correlated with formal, but not informal communication satisfaction. Formal communication satisfaction was significantly correlated with job satisfaction and organizational commitment. Conversely, informal communication satisfaction was significantly correlated with job satisfaction, but was not related to organizational commitment. Finally, job satisfaction was significantly correlated with organizational commitment and negatively correlated with turnover intention. Moreover, organizational commitment was negatively correlated with turnover intention. The implications of this research for human resources management within fashion companies are discussed in the concluding section of this paper.

Distributed genetic algorithm (DGA), also known as island model or coarse-grained model, is a kind of parallel genetic algorithm, in which a population is partitioned into several sub-populations and each of them evolves with its own genetic operators to maintain diversity of individuals. It is known that DGA is superior to conventional genetic algorithm with a single population in terms of solution quality and computation time. Several researches have been conducted to evaluate effects of parameters on GAs, but there is no research work yet that deals with structure of DGA. In this study, we tried to evaluate performance of various genetic algorithms (GAs) for the famous symmetric traveling salesman problems. The considered GAs include a conventional serial GA (SGA) with IGX (Improved Greedy Crossover) and several DGAs with various combinations of crossover operators such as OX (Order Crossover), DPX (Distance Preserving Crossover), GX (Greedy Crossover), and IGX. Two distinct immigration policies, conventional noncompetitive policy and newly proposed competitive policy are also considered. To compare performance of GAs clearly, a series of analysis of variance (ANOVA) is conducted for several scenarios. The experimental results and ANOVAs show that DGAs outperform SGA in terms of computation time, while the solution quality is statistically the same. The most effective crossover operators are revealed as IGX and DPX, especially IGX is outstanding to improve solution quality regardless of type of GAs. In the perspective of immigration policy, the proposed competitive policy is slightly superior to the conventional policy when the problem size is large.

The purpose of this study was to identify images of saleswomen by uniform and body type and to determine if the images have an effect on customer satisfaction and revisiting intention. This study was conducted between February 10th and February 23rd 2015, using a questionnaire to collect data from 608 adults from Seoul, Deajeon, and Chungnam Province. A 2×2 (body type×clothes) factorial experimental design was used. Frequency, factor, and reliability analysis, analysis of variance, one-way ANOVA, Tukey test, and multiple regression analysis methods were used to analyze data. The study results were as follows: First, images of saleswomen with different uniform and body types were classified based on the following three factors: professionalism, kindness and attractiveness. Second, the saleswomen's uniforms had significant impact on perceived attractiveness, with women who wore skirt suits being identified as more attractive than women with pant suits. The saleswomen's body types had significant effect on professionalism, kindness and attractiveness. Women with average body types were perceived positively in terms of professionalism and attractiveness, whilst women with large body types were perceived positively in terms of kindness. Third, the combination of uniform and body type had a significant effect on perceived professionalism. Women with average body types wearing pant suits were perceived to have high degree of professionalism and women with large body types wearing skirt suits were evaluated to have high professionalism. Fourth, the images described as attractive and kind for both uniform and body type had a positive influences on customer satisfaction and revisiting intention.

This research aimed to examine the effect of emotional dissonance and emotional intelligence on the prosocial behavior of fashion salespeople in department stores, and whether emotional intelligence mediates the relationship between emotional dissonance and prosocial behavior. Moreover, we aimed to suggest a method to improve the prosocial behavior of salespeople as a strategy to obtain a continuous competitive advantage in an increasingly competitive fashion distribution environment. This research was conducted through a questionnaire survey, and 345 responses were collected from department store salespeople for the final analysis. First, the analysis results showed that the emotional dissonance of salespeople arose from their dealings with their organization and with customers. Prosocial behavior was deduced to be a factor of the cooperation with coworker and extra-role customer service. The emotional intelligence was deduced to be a factor of the use of emotion, regulation of emotion, self-emotion appraisal, and others'emotion appraisal. Second, with a higher level of emotional dissonance against the organization, there was less cooperation with coworker, while a higher emotional dissonance against customers resulted in increased cooperation with coworker. Third, it appeared that with a higher level of emotional dissonance against the organization, there was a higher utilization of use of emotion, self-emotion appraisal, and others'emotion appraisal of emotional intelligence. Fourth, as the regulation of emotion, self-emotion appraisal, and use of emotion were higher, there was more cooperation with coworker, whereas an increase in the utilization of one's own emotion and emotional control resulted in a higher level of extra-role customer service. Finally, emotional intelligence has a significant mediating effect between emotional dissonance and prosocial behavior. The above results suggest that for department stores to improve the prosocial behavior of their sales staff requires the establishment of a method to enhance the emotional intelligence of the staff. The results also indicate that there is a need for department stores to prepare a systemic tool to enable them to select people with a high degree of emotional intelligence when recruiting salespeople.

The purpose of this study was to investigate factors influencing sales of health functional foods by door-to-door saleswomen. A total of 450 women who worked as door-to-door salespersons in Seoul were enrolled. The survey questionnaire was composed of five parts as follows: general characteristics, factors related with door-to-door sales process, task education, competency required for door-to-door salespersons, and customer relationship beliefs. The survey was conducted in October 2011. Finally, data on 302 subjects were statistically analyzed using the SPSS 17.0 package program. Reason for sales of health functional foods (p<0.01), time required for sales promotion (p<0.001), difficulties during sales of health functional foods (p<0.05), satisfaction of task education (p<0.01), and failure of salesperson's memory as problems of task education (p<0.01) were significantly associated with sales of health functional foods. However, means of sales promotion, frequency and time of task education, and competency required for door-to-door salespersons were not significantly related with sales of health functional foods. Customer relationship beliefs did not show significant association with sales of health functional foods either. In conclusion, certain factors were associated with sales of health functional foods by door-to-door saleswomen. These results provide an understanding for sales of door-to-door health functional foods and provide basic information for preparation of task education for health functional food saleswomen and marketing.

This research used an experimental design in an effort to assess the influence of brand gender and salespeople on the attitudes toward brands according to the males' gender identity traits. The study used a three-way split-plot experimental design, and data were analyzed by t-tests, and ANOVA. The subject of this research was men in their 20s and 30s, and a total of 178 people were selected through convenience- sampling. The findings are as follows: first, masculine male consumers preferred masculinity fashion brands; however, androgynous consumers preferred brands that reflect androgyny. Second, there were no differences in brand attitude according to the gender of the salesperson for the masculinity group, but the androgynous group estimated the brands as better when the salesperson was female. Third, there were no differences in the brand attitudes among consumers according to gender of the salesperson for the Galaxy; however, for Solid Homme, brand preference was stronger when the salesperson was a woman. Fourth, the influence of brand gender and salesperson gender on brand attitudes differed according to the gender of the consumer. Therefore, apparel companies must clearly understand the characteristics of consumer gender identity and execute proper marketing strategies in order to induce stronger positive attitudes toward their brands. Moreover, apparel companies should perceive that brand gender and the gender of the salesperson can consequently encourage brand preferences.

The study focuses on verifying the effects of service education and empowerment on job satisfaction, job performance, and customer orientation. 290 salespeople working for fashion companies participated by completing a survey. The collected data was then analyzed with SPSS 16.0 and AMOS 7.0. Structural equation modeling was used to examine the goodness of fit. Looking at the results of this study, the service education of salespersons in fashion companies was shown to affect their level of satisfaction with their compensation, whereas empowerment affected their psychological satisfaction. These findings indicate that the service training and empowerment as experienced by salespersons working for fashion companies affect their customer orientation and job performance. Specifically, psychological satisfaction as part of the overall level of job satisfaction was found directly to affect their customer orientation, whereas their satisfaction with their compensation did not affect their customer orientation. Customer-orientation as influenced by service education and empowerment was revealed to have direct effect on job performance. The results of this study indicate that the service education of salesperson working for fashion companies and their level of empowerment create job satisfaction and customer orientation in these individuals. This study will be a valuable source of information for those who create salesperson empowerment programs and salesperson management strategies for fashion companies. Such programs and management strategies can facilitate efficient job performance by salespersons working for fashion companies and increase their level of job satisfaction.

Traveling salesman problem is to minimize the total cost for a traveling salesman who wants to make a tour given finite number of cities along with the cost of travel between each pair them, visiting each cities exactly once before returning home. Traveling salesman problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study suggests a hybrid parallel genetic algorithm(HPGA) for traveling salesman problem The suggested algorithm combines parallel genetic algorithm, nearest neighbor search, and 2-opt. The suggested algorithm has been tested on 7 problems in TSPLIB and compared the results of existing methods(heuristics, meta-heuristics, hybrid, and parallel). Experimental results shows that HPGA could obtain good solution in total travel distance minimization.

Our interest in this paper is in the efficient computation of a good low bound for the traveling salesman problem and is in the application of a network problem in agriculture. We base our approach on a relatively new formulation of the TSP as a two-commodity network flow problem. By assigning Lagrangian multipliers to certain constraints and relaxing them, the problem separates into two single-commodity network flow problems and an assignment problem, for which efficient algorithms are available.