DSpace collection: 第27卷第2期
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Green Performance Assessment for Retail Industry in Taiwan
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109387
title: Green Performance Assessment for Retail Industry in Taiwan abstract: The retail industry in Taiwan plays an important role in people’s lives and influences consumers’ purchasing behavior. Due to global warming and the depletion of energy and other resources, most retailers are required to obey the green policy of reuse, recycling, and reduction in their operational process, service, and products. Therefore, we first evaluated the environmental performance of retailers using selected green criteria. Then, we assessed the performance of sustainable environmental practices among ten selected retailers using grey relation analysis and the entropy method to derive objective weights for the selected criteria. Next, for continuous improvement of retailers’ green performance, we extracted and summarized a self-assessment checklist selected from the questionnaire. Retailers can use the checklist for guidelines for continuous improvement.
<br>Interpreting Weights in Multiple Criteria Decision Making
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109386
title: Interpreting Weights in Multiple Criteria Decision Making abstract: Many decision making problems of business and management are formulated in terms of Multiple Attribute Decision Making (MADM): given a set of alternatives evaluated with multiple criteria, find the alternative which according to the Decision Maker (DM), has the most preferred combination of criteria values (attributes), or rank alternatives from the most preferred one to the least preferred one. The MADM methods incorporate mechanisms of building preference models based on information obtained from the DM. In a wide variety of such methods, the DM is supposed to provide information in terms of weights of criteria, usually understood as criteria’s priorities. These weights serve as parameters of the method-pecific preference models. The DM can define weights directly, or by using special weight elicitation techniques such as AHP, MAVT and others. Our concerns are that when using weight-based methods, the DM cannot ensure the correctness of the preference model. First, different weight-based methods use different kinds of preference models, which prioritize criteria based on weights in different manners. Second, interpretation of weights in some MADM methods is far from intuitive. Thus, a situation may occur when an inexperienced DM thinks of weights differently than they actually work in the method, and expresses the preference information incorrectly. In this paper we demonstrate the differences between how weights are interpreted in several methods: simple additive weighting, TOPSIS, VIKOR and PROMETHEE. We do it by comparing rankings produced with methods based on randomly generated data. We demonstrate that differences of interpreting weights significantly contribute to differences in produced rankings. A solution to this problem could be twofold: first, increasing awareness of differences between method-specific weight-based prioritizing mechanisms, and second, providing interpretations of weights for popular methods in the language understandable by the DMs.
<br>The Problem of Distribution of Park-and-Ride Car Parks in Warsaw
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109385
title: The Problem of Distribution of Park-and-Ride Car Parks in Warsaw abstract: The development of cities and agglomerations brings new problems to be solved. One of them is the excessive road traffic and the related air pollution. Heavy traffic causes ongestions and thus increases the pollution level, because one of the most significant sources of air pollution are car exhaust gases. It is known that the public transport produces less pollution per one passenger then the private one. On the basis of this fact the idea of the Park-and-Ride (P&R or P+R) was developed, where commuters travel to the borders of the city by their cars and from there they continue their trip by public transportation. In this work, we will concentrate on finding the best localizations for P&R points. Our approach is composed of two steps. In the first step, a number of communication hubs is selected where P&R can be located (feasibility analysis). In the second ste a subset of hubs is chosen to actually have P&R points built (commuters’ convenience analysis). We solve the P&R location problem on the first step using some aspects of the Hub and Spoke method by applying a specialized evolutionary algorithm. As the problem of the second step is rather small, we propose to have it solved by experts.
<br>A Queueing Model for Tiered Inspection Lines in Airports
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109384
title: A Queueing Model for Tiered Inspection Lines in Airports abstract: This paper proposes a tiered inspection system for airport security, wherein passengers are divided into three classes based on historical security records. A two-dimensional Markov process and a Markov modulated Poisson process (MMPP) queue were used in the formu- lation of the security inspection system. Simulated annealing was then used to obtain near- optimum solution for the model. The efficacy of the proposed model was evaluated using the arrival data of passengers at Taoyuan International Airport and other two international airports. A comparison with two conventional queueing models with regard to the average waiting time demonstrated the effectiveness of the proposed security inspection system in enhancing service efficiency and boosting the level of security.
<br>Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109383
title: Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints abstract: Sequential pattern mining is to discover frequent sequential patterns in a sequence database. The technique is applied to fields such as web click-stream mining, failure forecast, and traf- fic analysis. Conventional sequential pattern-mining approaches generally focus only the orders of items; however, the time interval between two consecutive events can be a valuable information when the time of the occurrence of an event is concerned. This study extends the concept of the well-known pattern growth approach, PrefixSpan algorithm, to propose a novel sequential pattern mining approach for sequential patterns with time intervals. Unlike the other time-interval sequential pattern-mining algorithms, the approach concerns the time
for the next event to occur more than the timing information with its precedent events. To obtain a more reliable sequential pattern, a new measure of the confidence of a sequential pattern is defined. Experiments are conducted to evaluate the performance of the proposed approach.
<br>A Generalized PROMETHEE III with Risk Preferences on Losses and Gains
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109382
title: A Generalized PROMETHEE III with Risk Preferences on Losses and Gains abstract: This study aims to generalize the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) III model by introducing risk preferences of decision makers. The risk preferences are expressed by an S-shaped value function with gain and loss parts. This study then illustrates an environmental evaluation of waste treatment plants for waste electrical and electronic equipment (WEEE) in Taiwan. Sensitivity analysis and the rank test demonstrate that the proposed model is rather stable. The PROMETHEE methods have been involved in various applications, especially in environmental management. One core process of PROMETHEE is to establish a preference difference function with two types of thresholds. The range of the slope lines of the linear preference is within the interval of [0, 1]. Working from the concept of the prospect theory, we extend its S-shaped function to the interval range of [−1, 1] so as to express risk preferences
that occur in two quadrants. This research assesses a project on 15 local WEEE treatment plants to promote their recycling capability and technology competitiveness. According to the five aspects, the performance measures of the plants are obtained from a field study. The proposed model has an advantage on rank invariance by changing the thresholds in our case with sensitivity analysis demonstrating the robustness of the model. The generalized PROMETHEE III
with risk preferences indeed provides an extension for making a decision in an uncertain environment.
<br>Multiple Criteria Analysis of the Airport Terminal Effectiveness by Multi-objective Optimization and Simulation
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109381
title: Multiple Criteria Analysis of the Airport Terminal Effectiveness by Multi-objective Optimization and Simulation abstract: A rational approach to terminal airport management is not a trivial task due to relatively complex interactions between passengers and terminal infrastructure. Such infrastructure may be represented or modelled as a network of service nodes. To make a decision about such a network structure, one has to take into account not only the cost of terminal infrastructure, but also a set of quality indicators depicting passenger service level. Such decision problems may be formulated in the multiple criteria setting. We propose a bi-criteria decision making problem with a discrete-event simulation model of a terminal airport as a base model. The simulation model is used to evaluate a finite set of configurations representing a network of service nodes. To point out the most preferred Pareto optimal configuration, we propose to use an interactive decision making method to navigate Pareto optimal solutions with so-called vectors of concessions and reference points as preference carriers. Such versatile decision making scheme may be used to solve practical multiple criteria decision problems with values of criteria functions obtained by simulation runs.
<br>Market Collective Wisdom Discovery for Portfolio Investments
https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109380
title: Market Collective Wisdom Discovery for Portfolio Investments abstract: The goal of numerous investing strategies, as opposed to hedging strategies, is “to beat the market”, i.e. to secure returns higher than those guaranteed by tracking market indices. In order to achieve this goal, one needs to identify key factors which drive markets and cause security prices to fluctuate. We assume that distinctive key market factors exist, though it is not known how such factors correlate and aggregate, and eventually push a market from one quotation to another. In other words, we purport that at a given time there is the collective wisdom in a market
which shapes the collective investment pattern for the future. We engage ourselves to reverse engineer that wisdom. Specifically, we attempt to reverse engineer it from market returns (which we interpret as collective market wisdom embodiment) with the use of the notions of vectors of concessions and compromise half lines, recently introduced into Multiple Criteria Decision Analysis. We illustrate our approach with preliminary calculations for selecting portfolios of international investment funds.
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