This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

This paper considers a special case of a three machine flow shop scheduling problem in which operation processing time of each job is ordered such that machine 1 has the longest processing time, whereas machine 3, the shortest processing time. The objective of the problem is the minimization of the total completion time. Although the problem is simple, its complexity is yet to be established to our best knowledge. This paper first introduces the problem and presents some optimal properties of the problem. Then, it establishes several special cases in which a polynomial-time optimal solution procedure can be found. In addition, the paper proves that the recognition version of the problem is at least binary NP-complete. The complexity of the problem has been open despite its simple structure and this paper finally establishes its complexity. Finally, a simple and intuitive heuristic is developed and the tight worst case bound on relative error of 6/5 is established.

In this manuscript, a modified single sampling plan is proposed for the inspection of products in which the nonconforming items can be classified in to two categories namely critical and non-critical; and explained with the help of industrial example. The operating procedure of this plan is also proposed and the performance measures such as the probability of acceptance, average sample number, average total inspection and average out going quality are also derived. The optimal parameters are determined which will have minimum sample size. The efficiency of the proposed plan is also discussed over the conventional single sampling plan. The extensive tables for selecting a modified single sampling plan based on AQL and LQL are provided for both Binomial and Poisson distributions and explained with the help of industrial data.

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

Every service firm must find ways to attract new customers, retain existing customers, and remain competitive and profitable. As competition increases, delivering better service becomes more important. Service quality is considered as a vital aspect for the success of the firms. Restaurant cannot be separated from the service quality they have to deliver. The development of restaurant is supported with the reputation of the country where the food comes from. Recently, one of the most trending topic is Korean wave which affects the Korean cuisine. A fuzzy AHP was employed to evaluate the service quality. It is more preferable than traditional AHP which is criticized for its inability to handle the uncertainty of the decision maker's perception. Six attributes are used to evaluate five Korean restaurants in Semarang, Indonesia. The result shows that innovation is the most important attribute. It seems that decision makers viewed the food variation and new method service as main factors that the restaurants have to manage. This finding can provide the managers with valuable insights into the attribute that reflects customers' perceptions; also to position their service based on their competitors. Validating the scale in other culture-based restaurants is an interesting area to be pursued.

Due to the large scale of Antarctic science, scientific collaboration is required for conducting scientific research. In this study, we attempted to investigate collaboration network and the role of research station in Antarctic science based on bibliometric data from 1995 to 2014. We confirmed that geographical proximity tends to be important for scientific collaboration by employing community detection in the network. This result raises the question about what the role of research station in Antarctica is. We tried to reveal its role by focusing on five countries, Belgium, China, Czech Republic, India, and Korea that constructed new research stations during the last decade. Relative growth rate, a value to measure the growth of publications, didn't differ much around the construction period compared to those in other periods for these countries except Belgium. However, we found geographical keywords emerged around the construction for all five countries. These keywords were utilized to observe national research activities in Antarctica. They show where countries started to be concerned about after the construction.

During the last two decades, impact factor has been widely used as a journal evaluation metric that differentiates the influence of a specific journal compared with other journals. However, impact factor does not provide a reliable metric between journals in different subject categories. For example, higher impact factors are given to biology and general sciences than those assigned to other traditional engineering and social sciences. This study initially analyzes the trend of the time series of the impact factors of the journals listed in Journal Citation Reports during the last decade. This study then proposes new journal evaluation metrics that adjust the impact factors across different subject categories. The proposed metrics possibly provides a consistent measure to mitigate the differences in impact factors among subject categories. On the basis of experimental results, we recommend the most reliable and appropriate metric to evaluate journals that are less dependent on the characteristics of subject categories.

With the growing interest in skincare and maintenance, there are increasing numbers of studies on the classification of skin type and the factors influencing each type. This study presents a novel methodology by using data mining, for the determination of the relationships between skin type, lifestyle, and patterns of cosmetic utilization. Eight skin-specific factors, which are moisture, sebum in U-zone (both cheeks), sebum in T-zone (forehead, nose, and chin), pore, melanin, wrinkle, acne, hemoglobin, were measured in 1,246 subjects living in South Korea, in conjunction with a questionnaire survey analyzing their lifestyles and pattern of cosmetic utilization. Using various multivariate statistical methods and data mining techniques, we classified the skin types based on the skin-specific values, determined the relationship between skin type and lifestyle, and accordingly sorted the subjects into clusters. Logistic regression analysis revealed gender-related differences in the skin; therefore, separate analyses were performed for males and females. Using the Gaussian Mixture Modeling (GMM) technique, we classified the subjects based on skin type (two male and four female). Using the ANOVA and decision tree techniques, we attempted to characterize the relationship between each skin type and the lifestyles of the subjects. Menstruation, eating habits, stress, and smoking were identified as the major factors affecting the skin.