Search results for: multi-criteria group decision making problems

Authors: Z. Ulukan, E. Demircioğlu

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Facility location is a complex real-world problem which needs a strategic management decision. This paper provides a general review on studies, efforts and developments in Facility Location Problems which are classical optimization problems having a wide-spread applications in various areas such as transportation, distribution, production, supply chain decisions and telecommunication. Our goal is not to review all variants of different studies in FLPs or to describe very detailed computational techniques and solution approaches, but rather to provide a broad overview of major location problems that have been studied, indicating how they are formulated and what are proposed by researchers to tackle the problem. A brief, elucidative table based on a grouping according to “General Problem Type” and “Methods Proposed” used in the studies is also presented at the end of the work.

Keywords: Discrete location problems, exact methods, heuristic algorithms, single source capacitated facility location problems.

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Authors: Mehmet Altınöz

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This study focuses on bureau management technologies and information systems in developing countries. Developing countries use such systems which facilitate executive and organizational functions through the utilization of bureau management technologies and provide the executive staff with necessary information. The concepts of data and information differ from each other in developing countries, and thus the concepts of data processing and information processing are different. Symbols represent ideas, objects, figures, letters and numbers. Data processing system is an integrated system which deals with the processing of the data related to the internal and external environment of the organization in order to make decisions, create plans and develop strategies; it goes without saying that this system is composed of both human beings and machines. Information is obtained through the acquisition and the processing of data. On the other hand, data are raw communicative messages. Within this framework, data processing equals to producing plausible information out of raw data. Organizations in developing countries need to obtain information relevant to them because rapid changes in the organizational arena require rapid access to accurate information. The most significant role of the directors and managers who work in the organizational arena is to make decisions. Making a correct decision is possible only when the directors and managers are equipped with sound ideas and appropriate information. Therefore, acquisition, organization and distribution of information gain significance. Today-s organizations make use of computer-assisted “Management Information Systems" in order to obtain and distribute information. Decision Support System which is closely related to practice is an information system that facilitates the director-s task of making decisions. Decision Support System integrates human intelligence, information technology and software in order to solve the complex problems. With the support of the computer technology and software systems, Decision Support System produces information relevant to the decision to be made by the director and provides the executive staff with supportive ideas about the decision. Artificial Intelligence programs which transfer the studies and experiences of the people to the computer are called expert systems. An expert system stores expert information in a limited area and can solve problems by deriving rational consequences. Bureau management technologies and information systems in developing countries create a kind of information society and information economy which make those countries have their places in the global socio-economic structure and which enable them to play a reasonable and fruitful role; therefore it is of crucial importance to make use of information and management technologies in order to work together with innovative and enterprising individuals and it is also significant to create “scientific policies" based on information and technology in the fields of economy, politics, law and culture.

Keywords: Bureau Management, Information Systems.

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Authors: Joseph Ignagni, Rebecca E. Deen

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There are many views on how human decision makers behave. In this work, the Justices of the United States Supreme Court will be viewed in terms of constrained maximization and cognitivecybernetic theory. This paper will integrate research in such fields as law, political science, psychology, economics and decision making theory. It will be argued that due to its heavy workload, the Supreme Court is forced to make decisions in a boundedly rational manner. The ideas and theory put forward here will be tested in the area of the Court’s decisions involving religion. Therefore, the cases involving the U.S. Constitution’s Free Exercise Clause and Establishment Clause will be analyzed. Also, variables such as the U.S. government’s involvement in these cases will be considered. The years to be studied will be 1987-2011.

Keywords: Establishment Clause, Free Exercise Clause, U.S. Constitution, U.S. Supreme Court.

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Authors: Leila Mohammadi

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This paper presents the impact of persuasive communication implemented by fertility clinics websites, and how this information influences women at their decision-making for undertaking this procedure. The influential factors for women decisions to do social egg freezing (SEF) are analyzed from a framing theory perspective, with a specific focus on the impact of persuasive information on women’s decision making. This study follows a quantitative approach. A two-phase survey has been conducted to examine the interest rate to undertake SEF. In the first phase, a questionnaire was available during a month (May 2015) to women to answer whether or not they knew enough information of this process, with a total of 230 answers. The second phase took place in the two last weeks of July 2015. All the respondents were invited to a seminars called ‘All about egg freezing’ and afretwards they were requested to answer the second questionnaire. After the seminar, in which they were given an extensive amount of information about egg freezing, a total of 115 women replied the questionnaire. The collected data during this process were analyzed using descriptive statistics. Most of the respondents changed their opinion in the second questionaire which was after receiving information. Although in the first questionnaire their self-evaluation of having knowledge about this process and the implemented technologies was very high, they realized that they still need to access more information from different sources in order to be able to make a decision. The study reached the conclusion that persuasive and framed information by clinics would affect the decisions of these women. Despite the reasons women have to do egg freezing and their motivations behind it, providing people necessary information and unprejudiced data about this process (such as its positive and negative aspects, requirements, suppositions, possibilities and consequences) would help them to make a more precise and reasonable decision about what they are buying.

Keywords: Decision making, fertility clinics, framing theory, persuasive information, social egg freezing.

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: Boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones.

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: Decision Making, Destination Choice, International Tourist, Pull Factor, Push Factor, Thailand, Travel Motivation.

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network.

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Authors: Hyun-Woo Cho

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The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: S. Sabbour, H. Lasi, P. von Tessin

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The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.

Keywords: Business Intelligence, decision support, strategic decisions, simulation, SCM.

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Authors: Souleymane Oumtanaga, Kadjo Tanon Lambert, Koné Tiémoman, Tety Pierre, Kimou KouadioProsper

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Multicast transmissions allow an host (the source) to send only one flow bound for a group of hosts (the receivers). Any equipment eager to belong to the group may explicitly register itself to that group via its multicast router. This router will be given the responsibility to convey all information relating to the group to all registered hosts. However in an environment in which the final receiver or the source frequently moves, the multicast flows need particular treatment. This constitutes one of the multicast transmissions problems around which several proposals were made in the Mobile IPv6 case in general. In this article, we describe the problems involved in this IPv6 multicast mobility and the existing proposals for their resolution. Then architecture will be proposed aiming to satisfy and optimize these transmissions in the specific case of a mobile multicast receiver in NC-HMIPv6 environment.

Keywords: Mobile IP, NC-HMIPv6, Multicast, MLD, PIM, SSM, Rendezvous Point.

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Authors: Mitchell J. McHugh, John J. Case

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Systems engineering is a holistic discipline that seeks to organize and optimize complex, interdisciplinary systems. With the growth of artificial intelligence, systems engineers must face the challenge of leveraging artificial intelligence systems to solve complex problems. This paper analyzes the integration of systems engineering and artificial intelligence and discusses how artificial intelligence systems embody the systems decision process (SDP). The SDP is a four-stage problem-solving framework that outlines how systems engineers can design and implement solutions using value-focused thinking. This paper argues that artificial intelligence models can replicate the SDP, thus validating its flexible, value-focused foundation. The authors demonstrate this by developing a machine vision mobile application that can classify weapons to augment the decision-making role of an Army subject matter expert. This practical application was an end-to-end design challenge that highlights how artificial intelligence systems embody systems engineering principles. The impact of this research demonstrates that the SDP is a dynamic tool that systems engineers should leverage when incorporating artificial intelligence within the systems that they develop.

Keywords: Computer vision, machine learning, mobile application, systems engineering, systems decision process.

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: Brain machine interface, decision-making, local field potentials, mobile robot, navigation, neural network, rat, signal processing.

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Authors: A. M. Qahtani, G. B. Wills, A. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: Customisation Software Products, Global Software Engineering, Local Decision Making, Requirement Engineering, Simulation Model.

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.

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Authors: I. McCulloh, A. Placona, D. Stewart, D. Gause, K. Kiernan, M. Stuart, C. Zinner, L. Cartwright

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We find in our data that an alarming number of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. We observe as many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient-specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision-makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.

Keywords: Decision science, KDPI, optimism bias, organ transplant.

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Authors: Amit Kumar, Pushpinder Singh, Parampreet Kaur, Amarpreet Kaur

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Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Systems with Applications 36 (2009) 6833-6842) is incorrect. The main aim of this paper is to propose a new approach for the ranking of generalized trapezoidal fuzzy numbers. The main advantage of the proposed approach is that the proposed approach provide the correct ordering of generalized and normal trapezoidal fuzzy numbers and also the proposed approach is very simple and easy to apply in the real life problems. It is shown that proposed ranking function satisfies all the reasonable properties of fuzzy quantities proposed by Wang and Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).

Keywords: Ranking function, Generalized trapezoidal fuzzy numbers

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: Information security risk treatment, Selection of risk measures, Risk acceptance and Multi-objective optimization.

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Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen

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The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model

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Authors: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: Embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems.

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Authors: N. Mantalay, N. Chakpitak, W. Janchai, P. Sureepong

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Work-life balance has been acknowledged and promoted for the sake of employee retention. It is essential for a manager to realize the human resources situation within a company to help employees work happily and perform at their best. This paper suggests knowledge management and critical thinking are useful to motivate employees to think about their work-life balance. A qualitative case study is presented, which aimed to discover the meaning of work-life balance-s meaning from the perspective of Thai knowledge workers and how it affects their decision-making towards work resignation. Results found three types of work-life balance dimensions; a work- life balance including a workplace and a private life setting, an organizational working life balance only, and a worklife balance only in a private life setting. These aspects all influenced the decision-making of the employees. Factors within a theme of an organizational work-life balance were involved with systematic administration, fair treatment, employee recognition, challenging assignments to gain working experience, assignment engagement, teamwork, relationship with superiors, and working environment, while factors concerning private life settings were about personal demands such as an increasing their salary or starting their own business.

Keywords: knowledge management, work-life balance, knowledge workers, decision-making, critical thinking, diverse workforce

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Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson, Göran Falkman

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Data mining has been used very frequently to extract hidden information from large databases. This paper suggests the use of decision trees for continuously extracting the clinical reasoning in the form of medical expert-s actions that is inherent in large number of EMRs (Electronic Medical records). In this way the extracted data could be used to teach students of oral medicine a number of orderly processes for dealing with patients who represent with different problems within the practice context over time.

Keywords: Data mining, Oral Medicine, Decision Trees, WEKA.

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Authors: H. Omrani, P. Gerber

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Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).

Keywords: Decision support tool, hybrid approach, urban mobility.

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Authors: J. Trarbach, S. Schosser, B. Vogt

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Decision-makers tend to prefer the first alternative over subsequent alternatives which is called the primacy effect. To reliably measure this effect, we conducted an experiment with real consequences for preference statements. Therefore, we elicit preferences of subjects using a rating scale, i.e. hypothetical preferences, and willingness to pay, i.e. real preferences, for two sequences of pain. Within these sequences, both overall intensity and duration of pain are identical. Hence, a rational decision-maker should be indifferent, whereas the primacy effect predicts a stronger preference for the first sequence. What we see is a primacy effect only for hypothetical preferences. This effect vanishes for real preferences.

Keywords: Decision making, primacy effect, real incentives, willingness to pay.

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner, David Gabriel F. de Barros

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Review researches are useful in terms of analysis of research problems. Between the types of review documents, we commonly find bibliometric studies. This type of application often helps the global visualization of a research problem and helps academics worldwide to understand the context of a research area better. In this document, a bibliometric view surrounding clustering techniques and sustainability problems is presented. The authors aimed at which issues mostly use clustering techniques and even which sustainability issue would be more impactful on today’s moment of research. During the bibliometric analysis, we found 10 different groups of research in clustering applications for sustainability issues: Energy; Environmental; Non-urban Planning; Sustainable Development; Sustainable Supply Chain; Transport; Urban Planning; Water; Waste Disposal; and, Others. Moreover, by analyzing the citations of each group, it was discovered that the Environmental group could be classified as the most impactful research cluster in the area mentioned. After the content analysis of each paper classified in the environmental group, it was found that the k-means technique is preferred for solving sustainability problems with clustering methods since it appeared the most amongst the documents. The authors finally conclude that a bibliometric assessment could help indicate a gap of researches on waste disposal – which was the group with the least amount of publications – and the most impactful research on environmental problems.

Keywords: Bibliometric assessment, clustering, sustainability, territorial partitioning.

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Authors: Javier Roca, Etienne Pugnaghi, Gaëtan Libert

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We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.

Keywords: Intelligent problem encoding, multiobjective decision making, evolutionary computing, RCPSP, resource leveling.

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: Case-based reasoning, decision tree, stock selection, machine learning.

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

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Authors: Sinchul Back, Sun Ho Kim, Jennifer LaPrade, Ilju Seong

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Due to the advantage of using the Internet, cybercriminals can reach target(s) without border controls. Prior research on criminology and crime science has largely been void of empirical studies on journey-to-cybercrime and crime opportunity. Thus, the purpose of this study is to understand more about cyber offender spatial decision making associated with crime opportunity factors (i.e., co-offending, offender-stranger). Data utilized in this study were derived from 306 U.S. Federal court cases of cybercrime. The findings of this study indicated that there was a positive relationship between co-offending and journey-to-cybercrime, whereas there was no link between offender-stranger and journey-to-cybercrime. Also, the results showed that there was no relationship between cybercriminal sex, age, and journey-to-cybercrime. The policy implications and limitations of this study are discussed.

Keywords: Co-offending, crime opportunity, journey-to-cybercrime, offender-stranger.

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

Abstract:

Waste load allocation (WLA) policies may use multiobjective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: Waste load allocation (WLA), Value index, Multi objective particle swarm optimization (MOPSO), Haraz River, Equity.

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Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

Abstract:

Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

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