Search results for: route selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1218

Search results for: route selection

1188 Project Selection by Using a Fuzzy TOPSIS Technique

Authors: M. Salehi, R. Tavakkoli-Moghaddam

Abstract:

Selection of a project among a set of possible alternatives is a difficult task that the decision maker (DM) has to face. In this paper, by using a fuzzy TOPSIS technique we propose a new method for a project selection problem. After reviewing four common methods of comparing investment alternatives (net present value, rate of return, benefit cost analysis and payback period) we use them as criteria in a TOPSIS technique. First we calculate the weight of each criterion by a pairwise comparison and then we utilize the improved TOPSIS assessment for the project selection.

Keywords: Fuzzy Theory, Pairwise Comparison, ProjectSelection, TOPSIS Technique.

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1187 Methodology: A Review in Modelling and Predictability of Embankment in Soft Ground

Authors: Bhim Kumar Dahal

Abstract:

Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: Embankment, ground improvement, modelling, model prediction.

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1186 Dynamic Reroute Modeling for Emergency Evacuation: Case Study of Brunswick City, Germany

Authors: Yun-Pang Flötteröd, Jakob Erdmann

Abstract:

The human behaviors during evacuations are quite complex. One of the critical behaviors which affect the efficiency of evacuation is route choice. Therefore, the respective simulation modeling work needs to function properly. In this paper, Simulation of Urban Mobility’s (SUMO) current dynamic route modeling during evacuation, i.e. the rerouting functions, is examined with a real case study. The result consistency of the simulation and the reality is checked as well. Four influence factors (1) time to get information, (2) probability to cancel a trip, (3) probability to use navigation equipment, and (4) rerouting and information updating period are considered to analyze possible traffic impacts during the evacuation and to examine the rerouting functions in SUMO. Furthermore, some behavioral characters of the case study are analyzed with use of the corresponding detector data and applied in the simulation. The experiment results show that the dynamic route modeling in SUMO can deal with the proposed scenarios properly. Some issues and function needs related to route choice are discussed and further improvements are suggested.

Keywords: Evacuation, microscopic traffic simulation, rerouting, SUMO.

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1185 Hub Port Positioning and Route Planning of Feeder Lines for Regional Transportation Network

Authors: Huang Xiaoling, Liu Lufeng

Abstract:

In this paper, we seek to determine one reasonable local hub port and optimal routes for a containership fleet, performing pick-ups and deliveries, between the hub and spoke ports in a same region. The relationship between a hub port, and traffic in feeder lines is analyzed. A new network planning method is proposed, an integrated hub port location and route design, a capacitated vehicle routing problem with pick-ups, deliveries and time deadlines are formulated and solved using an improved genetic algorithm for positioning the hub port and establishing routes for a containership fleet. Results on the performance of the algorithm and the feasibility of the approach show that a relatively small fleet of containerships could provide efficient services within deadlines.

Keywords: Route planning, Hub port location, Container feeder service.

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1184 Supplier Selection by Considering Cost and Reliability

Authors: K. -H. Yang

Abstract:

Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: Mixed integer programming, quantitative approach, supplier’s reliability, supplier selection.

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1183 A Rough-set Based Approach to Design an Expert System for Personnel Selection

Authors: Ehsan Akhlaghi

Abstract:

Effective employee selection is a critical component of a successful organization. Many important criteria for personnel selection such as decision-making ability, adaptability, ambition, and self-organization are naturally vague and imprecise to evaluate. The rough sets theory (RST) as a new mathematical approach to vagueness and uncertainty is a very well suited tool to deal with qualitative data and various decision problems. This paper provides conceptual, descriptive, and simulation results, concentrating chiefly on human resources and personnel selection factors. The current research derives certain decision rules which are able to facilitate personnel selection and identifies several significant features based on an empirical study conducted in an IT company in Iran.

Keywords: Decision Making, Expert System, PersonnelSelection, Rough Set Theory

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1182 Efficient Single Relay Selection Scheme for Cooperative Communication

Authors: Sung-Bok Choi, Hyun-Jun Shin, Hyoung-Kyu Song

Abstract:

This paper proposes a single relay selection scheme in  cooperative communication. Decode-and-forward scheme is  considered when a source node wants to cooperate with a single relay  for data transmission. To use the proposed single relay selection  scheme, the source node makes a little different pattern signal which is  not complex pattern and broadcasts it. The proposed scheme does not  require the channel state information between the source node and  candidates of the relay during the relay selection. Therefore, it is able  to be used in many fields.

Keywords: Relay selection, cooperative communication, df, channel codes.

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1181 Material Selection for a Manual Winch Rope Drum

Authors: Moses F. Oduori, Enoch K. Musyoka, Thomas O. Mbuya

Abstract:

The selection of materials is an essential task in mechanical design processes. This paper sets out to demonstrate the application of analytical decision making during mechanical design and, particularly, in selecting a suitable material for a given application. Equations for the mechanical design of a manual winch rope drum are used to derive quantitative material performance indicators, which are then used in a multiple attribute decision making (MADM) model to rank the candidate materials. Thus, the processing of mechanical design considerations and material properties data into information that is suitable for use in a quantitative materials selection process is demonstrated for the case of a rope drum design. Moreover, Microsoft Excel®, a commonly available computer package, is used in the selection process. The results of the materials selection process are in agreement with current industry practice in rope drum design. The procedure that is demonstrated here should be adaptable to other design situations in which a need arises for the selection of engineering materials, and other engineering entities.

Keywords: Design Decisions, Materials Selection, Mechanical Design, Rope Drum Design.

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1180 Determining the Criteria and their Importance Level of Calibration Supplier Selection

Authors: Ayse Gecer, Nihal Erginel

Abstract:

Quality control is the crucial step for ISO 9001 Quality System Management Standard for companies. While measuring the quality level of both raw material and semi product/product, the calibration of the measuring device is an essential requirement. Calibration suppliers are in the service sector and therefore the calibration supplier selection is becoming a worthy topic for improving service quality. This study presents the results of a questionnaire about the selection criteria of a calibration supplier. The questionnaire was applied to 103 companies and the results are discussed in this paper. The analysis was made with MINITAB 14.0 statistical programs. “Competence of documentations" and “technical capability" are defined as the prerequisites because of the ISO/IEC17025:2005 standard. Also “warranties and complaint policy", “communication", “service features", “quality" and “performance history" are defined as very important criteria for calibration supplier selection.

Keywords: Calibration, criteria of calibration supplier selection, calibration supplier selection, questionnaire

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1179 Intelligent Caching in on-demand Routing Protocol for Mobile Adhoc Networks

Authors: Shobha.K.R., K. Rajanikanth

Abstract:

An on-demand routing protocol for wireless ad hoc networks is one that searches for and attempts to discover a route to some destination node only when a sending node originates a data packet addressed to that node. In order to avoid the need for such a route discovery to be performed before each data packet is sent, such routing protocols must cache routes previously discovered. This paper presents an analysis of the effect of intelligent caching in a non clustered network, using on-demand routing protocols in wireless ad hoc networks. The analysis carried out is based on the Dynamic Source Routing protocol (DSR), which operates entirely on-demand. DSR uses the cache in every node to save the paths that are learnt during route discovery procedure. In this implementation, caching these paths only at intermediate nodes and using the paths from these caches when required is tried. This technique helps in storing more number of routes that are learnt without erasing the entries in the cache, to store a new route that is learnt. The simulation results on DSR have shown that this technique drastically increases the available memory for caching the routes discovered without affecting the performance of the DSR routing protocol in any way, except for a small increase in end to end delay.

Keywords: Caching, DSR, on demand routing, MANET.

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1178 The Effect of Increment in Simulation Samples on a Combined Selection Procedure

Authors: Mohammad H. Almomani, Rosmanjawati Abdul Rahman

Abstract:

Statistical selection procedures are used to select the best simulated system from a finite set of alternatives. In this paper, we present a procedure that can be used to select the best system when the number of alternatives is large. The proposed procedure consists a combination between Ranking and Selection, and Ordinal Optimization procedures. In order to improve the performance of Ordinal Optimization, Optimal Computing Budget Allocation technique is used to determine the best simulation lengths for all simulation systems and to reduce the total computation time. We also argue the effect of increment in simulation samples for the combined procedure. The results of numerical illustration show clearly the effect of increment in simulation samples on the proposed combination of selection procedure.

Keywords: Indifference-Zone, Optimal Computing Budget Allocation, Ordinal Optimization, Ranking and Selection, Subset Selection.

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1177 Evolutionary Feature Selection for Text Documents using the SVM

Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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1176 A Planning Model for Evacuation in Building

Authors: Hsin-Yun Lee, Hao-Hsi Tseng

Abstract:

Previous studies mass evacuation route network does not fully reflect the step-by-step behavior and evacuees make routing decisions. Therefore, they do not work as expected when applied to the evacuation route planning is valid. This article describes where evacuees may have to make a direction to select all areas were identified as guiding points to improve evacuation routes network. This improved route network can be used as a basis for the layout can be used to guide the signs indicate that provides the required evacuation direction. This article also describes that combines simulation and artificial bee colony algorithm to provide the proposed routing solutions, to plan an integrated routing mode. The improved network and the model used is the cinema as a case study to assess the floor. The effectiveness of guidance solution in the total evacuation time is significant by verification.

Keywords: Artificial bee colony, Evacuation, Simulation.

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1175 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis

Authors: Carlos Huertas, Reyes Juarez-Ramirez

Abstract:

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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1174 Unsupervised Feature Learning by Pre-Route Simulation of Auto-Encoder Behavior Model

Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in VerilogHDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: Auto-encoder, Behavior model simulation, Digital hardware design, Pre-route simulation, Unsupervised feature learning.

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1173 An Adequate Choice of Initial Sample Size for Selection Approach

Authors: Mohammad H. Almomani, Rosmanjawati Abdul Rahman

Abstract:

In this paper, we consider the effect of the initial sample size on the performance of a sequential approach that used in selecting a good enough simulated system, when the number of alternatives is very large. We implement a sequential approach on M=M=1 queuing system under some parameter settings, with a different choice of the initial sample sizes to explore the impacts on the performance of this approach. The results show that the choice of the initial sample size does affect the performance of our selection approach.

Keywords: Ranking and Selection, Ordinal Optimization, Optimal Computing Budget Allocation, Subset Selection, Indifference-Zone, Initial Sample Size.

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1172 Link Availability Estimation for Modified AOMDV Protocol

Authors: R. Prabha, N. Ramaraj

Abstract:

Routing in adhoc networks is a challenge as nodes are mobile, and links are constantly created and broken. Present ondemand adhoc routing algorithms initiate route discovery after a path breaks, incurring significant cost to detect disconnection and establish a new route. Specifically, when a path is about to be broken, the source is warned of the likelihood of a disconnection. The source then initiates path discovery early, avoiding disconnection totally. A path is considered about to break when link availability decreases. This study modifies Adhoc On-demand Multipath Distance Vector routing (AOMDV) so that route handoff occurs through link availability estimation.

Keywords: Mobile Adhoc Network (MANET), Routing, Adhoc On-demand Multipath Distance Vector routing (AOMDV), Link Availability.

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1171 Enhanced Bidirectional Selection Sort

Authors: Jyoti Dua

Abstract:

An algorithm is a well-defined procedure that takes some input in the form of some values, processes them and gives the desired output. It forms the basis of many other algorithms such as searching, pattern matching, digital filters etc., and other applications have been found in database systems, data statistics and processing, data communications and pattern matching. This paper introduces algorithmic “Enhanced Bidirectional Selection” sort which is bidirectional, stable. It is said to be bidirectional as it selects two values smallest from the front and largest from the rear and assigns them to their appropriate locations thus reducing the number of passes by half the total number of elements as compared to selection sort.

Keywords: Bubble sort, cocktail sort, selection sort, heap sort.

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1170 A Model for Test Case Selection in the Software-Development Life Cycle

Authors: Adtha Lawanna

Abstract:

Software maintenance is one of the essential processes of Software-Development Life Cycle. The main philosophies of retaining software concern the improvement of errors, the revision of codes, the inhibition of future errors, and the development in piece and capacity. While the adjustment has been employing, the software structure has to be retested to an upsurge a level of assurance that it will be prepared due to the requirements. According to this state, the test cases must be considered for challenging the revised modules and the whole software. A concept of resolving this problem is ongoing by regression test selection such as the retest-all selections, random/ad-hoc selection and the safe regression test selection. Particularly, the traditional techniques concern a mapping between the test cases in a test suite and the lines of code it executes. However, there are not only the lines of code as one of the requirements that can affect the size of test suite but including the number of functions and faulty versions. Therefore, a model for test case selection is developed to cover those three requirements by the integral technique which can produce the smaller size of the test cases when compared with the traditional regression selection techniques.

Keywords: Software maintenance, regression test selection, test case.

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1169 A Model for Test Case Selection in the Software-Development Life Cycle

Authors: Adtha Lawanna

Abstract:

Software maintenance is one of the essential processes of Software-Development Life Cycle. The main philosophies of retaining software concern the improvement of errors, the revision of codes, the inhibition of future errors, and the development in piece and capacity. While the adjustment has been employing, the software structure has to be retested to an upsurge a level of assurance that it will be prepared due to the requirements. According to this state, the test cases must be considered for challenging the revised modules and the whole software. A concept of resolving this problem is ongoing by regression test selection such as the retest-all selections, random/ad-hoc selection and the safe regression test selection. Particularly, the traditional techniques concern a mapping between the test cases in a test suite and the lines of code it executes. However, there are not only the lines of code as one of the requirements that can affect the size of test suite but including the number of functions and faulty versions. Therefore, a model for test case selection is developed to cover those three requirements by the integral technique which can produce the smaller size of the test cases when compared with the traditional regression selection techniques.

Keywords: Software maintenance, regression test selection, test case.

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1168 Towards a Systematic, Cost-Effective Approach for ERP Selection

Authors: Hassan Haghighi, Omid Mafi

Abstract:

Existing experiences indicate that one of the most prominent reasons that some ERP implementations fail is related to selecting an improper ERP package. Among those important factors resulting in inappropriate ERP selections, one is to ignore preliminary activities that should be done before the evaluation of ERP packages. Another factor yielding these unsuitable selections is that usually organizations employ prolonged and costly selection processes in such extent that sometimes the process would never be finalized or sometimes the evaluation team might perform many key final activities in an incomplete or inaccurate way due to exhaustion, lack of interest or out-of-date data. In this paper, a systematic approach that recommends some activities to be done before and after the main selection phase is introduced for choosing an ERP package. On the other hand, the proposed approach has utilized some ideas that accelerates the selection process at the same time that reduces the probability of an erroneous final selection.

Keywords: enterprise resource planning, evaluation and selectionof ERP packages, organizational readiness for employing ERP, evaluationlists.

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1167 Feature Subset Selection Using Ant Colony Optimization

Authors: Ahmed Al-Ani

Abstract:

Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classification task. Due to its importance, the problem of feature selection has been investigated by many researchers. In this paper, a novel feature subset search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.

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1166 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analyzing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics.

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1165 Selection Initial modes for Belief K-modes Method

Authors: Sarra Ben Hariz, Zied Elouedi, Khaled Mellouli

Abstract:

The belief K-modes method (BKM) approach is a new clustering technique handling uncertainty in the attribute values of objects in both the cluster construction task and the classification one. Like the standard version of this method, the BKM results depend on the chosen initial modes. So, one selection method of initial modes is developed, in this paper, aiming at improving the performances of the BKM approach. Experiments with several sets of real data show that by considered the developed selection initial modes method, the clustering algorithm produces more accurate results.

Keywords: Clustering, Uncertainty, Belief function theory, Belief K-modes Method, Initial modes selection.

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1164 TOPSIS Method for Supplier Selection Problem

Authors: Omid Jadidi, Fatemeh Firouzi, Enzo Bagliery

Abstract:

Supplier selection, in real situation, is affected by several qualitative and quantitative factors and is one of the most important activities of purchasing department. Since at the time of evaluating suppliers against the criteria or factors, decision makers (DMS) do not have precise, exact and complete information, supplier selection becomes more difficult. In this case, Grey theory helps us to deal with this problem of uncertainty. Here, we apply Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate and select the best supplier by using interval fuzzy numbers. Through this article, we compare TOPSIS with some other approaches and afterward demonstrate that the concept of TOPSIS is very important for ranking and selecting right supplier.

Keywords: TOPSIS, fuzzy number, MADM, Supplier selection

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1163 Bird Diversity along Boat Touring Routes in Tha Ka Sub-District, Amphawa District, Samut Songkram Province, Thailand

Authors: N. Charoenpokaraj, P. Chitman

Abstract:

This research aims to study species, abundance, status of birds, the similarities and activity characteristics of birds which reap benefits from the research area in boat touring routes in Tha Ka sub-district, Amphawa District, Samut Songkram Province, Thailand. from October 2012 – September 2013. The data was analyzed to find the abundance, and similarity index of the birds. The results from the survey of birds on all three routes found that there are 33 families and 63 species. Route 3 (traditional coconut sugar making kiln – resort) had the most species; 56 species. There were 18 species of commonly found birds with an abundance level of 5, which calculates to 28.57% of all bird species. In August, 46 species are found, being the greatest number of bird species benefiting from this route. As for the status of the birds, there are 51 resident birds, 7 resident and migratory birds, and 5 migratory birds. On Route 2 and Route 3, the similarity index value is equal to 0.881. The birds are classified by their activity characteristics i.e. insectivore, piscivore, granivore, nectrivore and aquatic invertebrate feeder birds. Some birds also use the area for nesting.

Keywords: Bird diversity, boat touring routes, Samut Songkram.

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1162 Hospital Facility Location Selection Using Permanent Analytics Process

Authors: C. Ardil

Abstract:

In this paper, a new MCDMA approach, the permanent analytics process is proposed to assess the immovable valuation criteria and their significance in the placement of the healthcare facility. Five decision factors are considered for the value and selection of immovables. In the multiple factor selection problems, the priority vector of the criteria used to compare several immovables is first determined using the permanent analytics method, a mathematical model for the multiple criteria decisionmaking process. Then, to demonstrate the viability and efficacy of the suggested approach, twenty potential candidate locations were evaluated using the hospital site selection problem's decision criteria. The ranking accuracy of estimation was evaluated using composite programming, which took into account both the permanent analytics process and the weighted multiplicative model. 

Keywords: Hospital Facility Location Selection, Permanent Analytics Process, Multiple Criteria Decision Making (MCDM)

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1161 Dynamic Network Routing Method Based on Chromosome Learning

Authors: Xun Liang

Abstract:

In this paper, we probe into the traffic assignment problem by the chromosome-learning-based path finding method in simulation, which is to model the driver' behavior in the with-in-a-day process. By simply making a combination and a change of the traffic route chromosomes, the driver at the intersection chooses his next route. The various crossover and mutation rules are proposed with extensive examples.

Keywords: Chromosome learning, crossover, mutation, traffic path finding.

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1160 Applying Fuzzy Decision Making Approach to IT Outsourcing Supplier Selection

Authors: Gülcin Büyüközkan, Mehmet Sakir Ersoy

Abstract:

The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourcing suppliers. An axiomatic design based fuzzy group decision making is adopted to evaluate supplier alternatives. Finally, a case study is given to demonstrate the potential of the methodology. KeywordsIT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic.

Keywords: IT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic

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1159 Selection of Solid Waste Landfill Site Using Geographical Information System (GIS)

Authors: F. Iscan, C. Yagci

Abstract:

Rapid population growth, urbanization and industrialization are known as the most important factors of environment problems. Elimination and management of solid wastes are also within the most important environment problems. One of the main problems in solid waste management is the selection of the best site for elimination of solid wastes. Lately, Geographical Information System (GIS) has been used for easing selection of landfill area. GIS has the ability of imitating necessary economic, environmental and political limitations. They play an important role for the site selection of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of environmental, social and cultural factors and maximum effect for engineering/economic factors for site selection of landfill areas and using GIS for a decision support mechanism in solid waste landfill areas site selection will be presented in Aksaray/Turkey city, Güzelyurt district practice.

Keywords: GIS, landfill, solid waste, spatial analysis.

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