• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.95-102
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• 2012

The development of applications for vehicular ad hoc networks (VANETs) has very specific and clear goals such as providing intellectual safe transport systems. An emergency warning technic for public safety is one of the applications which requires an intelligent broadcast mechanism to transmit warning messages quickly and efficiently against the time restriction. The broadcast storm problem causing several packet collisions and extra delay has to be considered to design a broadcast protocol for VANETs, when multiple nodes attempt transmission simultaneously at the access control layer. In this paper, we propose an early intelligent alert broadcasting (EI-CAST) algorithm to resolve effectively the broadcast storm problem and meet time-critical requirement. The proposed algorithm uses not only the early alert technic on the basis of time to collision (TTC) but also the intelligent broadcasting technic on the basis of fuzzy logic, and the performance of the proposed algorithm was compared and evaluated through simulation with the existing broadcasting algorithms. It was demonstrated that the proposed algorithm shows a vehicle can receive the alert message before a collision and have no packet collision when the distance of alert region is less than 4 km.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.1015-1029
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• 2011

Conventional MCDA techniques have been used in the field of water resources in the past. A GIS can offer an effective spatial data-handling tool that can enhance water resources modeling through interfaces with sophisticated models. However, GIS systems have a limited capability as far as the analysis of the value structure is concerned. The MCDA techniques provide the tools for aggregating the geographical data and the decision maker's preferences into a one-dimensional value for analyzing alternative decisions. In other words, the MCDA allows multiple criteria to be used in deciding upon the best alternatives. The combination of GIS and MCDA capabilities is of critical importance in spatial multi-criteria analysis. The advantage of having spatial data is that it allows the consideration of the unique characteristics at every point. The purpose of this study is to identify, review, and evaluate the performance of a number of conventional MCDA techniques for integration with GIS. Even though there are a number of techniques which have been applied in many fields, this study will only consider the techniques that have been applied in floodplain decision-making problems. Two different methods for multi-criteria evaluation were selected to be integrated with GIS. These two algorithms are Compromise Programming (CP), Spatial Compromise Programming (SCP). The target region for a demonstration application of the methodology was the Suyoung River Basin in Korea.