• Title/Summary/Keyword: multiple-decision method

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Multiple criteria decision making method for selecting of sealing element for earth dams considering long and short terms goals

  • Rashidi, Babak;Shirangi, Ehsan;Baymaninezhad, Matin
    • Wind and Structures
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    • v.26 no.2
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    • pp.69-74
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    • 2018
  • Nowadays, using math logic in great civil projects is considered by the clients to achieve the goals of project including quality optimization, costs, avoiding individual, emotional and political decision making, long-term and short-term goals and they are the main requirements of each project and should be considered by the decision makers to avoid the illogical decision making applied on the majority of civil projects and this imposes great financial and spiritual costs on our country. The present study attempts to present one of the civil projects (Ghasre Shirin storage dam) whose client was not ministry of energy for the first time and the short-term and long-term goals of the private sector were applied based on the triangle of quality, cost and time. Also, the math logic and model (multi-criteria decision making method and decision making matrix) is used in one of the most important sections of project, sealing element, policies and new materials (Geosynthetics) are considered and this leads to suitable decision making in this regard. It is worth to mention that this method is used for other sections of a dam including body, water diversion system, diaphragm and other sectors or in other civil projects of building, road construction, etc.

Temporal Search Algorithm for Multiple-Pedestrian Tracking

  • Yu, Hye-Yeon;Kim, Young-Nam;Kim, Moon-Hyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.5
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    • pp.2310-2325
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    • 2016
  • In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

Evaluation criterion for different methods of multiple-attribute group decision making with interval-valued intuitionistic fuzzy information

  • Qiu, Junda;Li, Lei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3128-3149
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    • 2018
  • A number of effective methods for multiple-attribute group decision making (MAGDM) with interval-valued intuitionistic fuzzy numbers (IVIFNs) have been proposed in recent years. However, the different methods frequently yield different, even sometimes contradictory, results for the same problem. In this paper a novel criterion to determine the advantages and disadvantages of different methods is proposed. First, the decision-making process is divided into three parts: translation of experts' preferences, aggregation of experts' opinions, and comparison of the alternatives. Experts' preferences aggregation is considered the core step, and the quality of the collective matrix is considered the most important evaluation index for the aggregation methods. Then, methods to calculate the similarity measure, correlation, correlation coefficient, and energy of the intuitionistic fuzzy matrices are proposed, which are employed to evaluate the collective matrix. Thus, the optimal method can be selected by comparing the collective matrices when all the methods yield different results. Finally, a novel approach for aggregating experts' preferences with IVIFN is presented. In this approach, experts' preferences are mapped as points into two-dimensional planes, with the plant growth simulation algorithm (PGSA) being employed to calculate the optimal rally points, which are inversely mapped to IVIFNs to establish the collective matrix. In the study, four different methods are used to address one example problem to illustrate the feasibility and effectiveness of the proposed approach.

An interactive face search procedure for multiple objective linear programming

  • Lee, Dong-Yeup
    • Korean Management Science Review
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    • v.10 no.2
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    • pp.11-26
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    • 1993
  • This paper presents a new interactive procedure for multiple objective linear programming problem (MOLP). In practical multiple objective linear programming applications, there is usually no need for the decision maker to consider solutions which are not efficient. Therefore, the interactive procedure presented here searches only among efficient solutions and terminates with a solution that is guaranteed to be efficient. It also can converge to nonextreme efficient final solutions rather than being restricted to only extreme efficient points of the feasible set. The procedure does not require sophisticated judgements or inputs from the decision maker. One of the most attractive features of the procedure however, is that the method allows the DM to examine the efficient faces it finds. As iteration goes, the DM can explore a wide variety of efficient faces rather than efficient faces confined to only certain subregion of the feasible set of problem MOLP since the efficient faces that the procedure finds need not be adjacent. This helps the DM explore the nature of the efficient set of problem MOLP and also helps the DM have confidence with a final solution. For these reasons, I feel that the procedure offer significant promise in solving multiple objective linear programs rapidly and in a satisfying manner to the DM.

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An assignment method for part-machine cell formation problem in the presence of multiple process routes

  • Won, You-Kyung;Kim, Sehun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1994.04a
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    • pp.236-243
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    • 1994
  • In this paper we consider the part-machine cell formation decision of the generalized Group Technology(GT) problem in which multiple process routes can be generated for each part. The existing p-median model and similarity coefficient algorithm can solve only small-sized or well-structured cases. We suggest an assignment method for the cell formation problem. This method uses an assignment model which is a simple linear programming. Numerical examples show that our assignment method provides good separable cells formation even for large-sized and ill-structured problems.

Acoustic Signal based Optimal Route Selection Problem: Performance Comparison of Multi-Attribute Decision Making methods

  • Borkar, Prashant;Sarode, M.V.;Malik, L. G.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.647-669
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    • 2016
  • Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

Clustering of Decision Making Units using DEA (DEA를 이용한 의사결정단위의 클러스터링)

  • Kim, Kyeongtaek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.4
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    • pp.239-244
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    • 2014
  • The conventional clustering approaches are mostly based on minimizing total dissimilarity of input and output. However, the clustering approach may not be helpful in some cases of clustering decision making units (DMUs) with production feature converting multiple inputs into multiple outputs because it does not care converting functions. Data envelopment analysis (DEA) has been widely applied for efficiency estimation of such DMUs since it has non-parametric characteristics. We propose a new clustering method to identify groups of DMUs that are similar in terms of their input-output profiles. A real world example is given to explain the use and effectiveness of the proposed method. And we calculate similarity value between its result and the result of a conventional clustering method applied to the example. After the efficiency value was added to input of K-means algorithm, we calculate new similarity value and compare it with the previous one.

Job sequencing decision in flow shop using revised Multi-Criteria Decision Making Method (수정된 다기준 의사결정을 이용한 흐름방식에서의 작업순서 결정)

  • 안춘수;강태건;정상윤;홍성일
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.44
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    • pp.135-151
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    • 1997
  • In this paper, we propose a simple and relatively efficient heuristic method to determine job sequencing in the flow-shop considering multiple criteria such as processing time, due date and cost. The proposed method is applicable to the flow- shop where the jobs are released simultaneously and their processing sequence is predetermined and not changed until the whole jobs are processed. To develop this method, we mixed and modified some well-known multi-attribute decision heuristics such as the simple linear weighting scheme, the lexicographic rule and the 'elimination by aspect' rule. Some computer simulations were conducted to test the efficiency of the proposed method and it has been compared with the SWPT (Shortest Working Processing Time) rule and EDD (Earliest Due Date) rule. The results show that our method is as effective as the traditional ones in terms of mean flow time, tardiness, makespan, cycle time, machine utilization, etc., and proved to be much simpler and more flexible to be used in real situations.

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MULTICRITERIA MODELS FOR GROUP DECISION MAKING : COMPROMISE PROGRAMMING VS. THE ANALYTIC HIERACHY PROCESS

  • Kwak, N.K.;McCarthy, Kevin J.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.16 no.1
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    • pp.97-112
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    • 1991
  • This paper describes two contrasting approaches to group decision making involving multiple criteria. A compromise programming method and the analytic hierarchy process are analyzed and compared by using an illustrative example of a computer model selection problem to demonstrate their usefulness as a viable tool for group decision making. This paper further considers some extensions and modifications of there two methods for future study.

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An Interactive Method for Multicriteria Simulation Optimization with Integer Variables (이산형 다기준 시뮬레이션 최적화를 위한 대화형 방법)

  • Shin, Wan-S.;Kim, Jae-Yong
    • Journal of Korean Institute of Industrial Engineers
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    • v.22 no.4
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    • pp.633-649
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    • 1996
  • An interactive multicriteria method, which is called the Modified Pairwise Comparison Stochastic Cutting Plane (MPCSCP) method, is proposed for determining the best levels of the integer decision variables needed to optimize a stochastic computer simulation with multiple response functions. MPCSCP combines good features from interactive tradeoff cutting plane methods and response surface methodologies. The proposed method uses a simple pairwise man-machine interaction and searches an integer space uniformly by using the experimental design which evaluates the decision space centering around an integer center point. The characteristics of the proposed method are investigated through an extensive computational study. The parameter configurations examined in the study are (1) variability of the sampling errors, (2) the size of experimental design, (3) the relaxation of cutting planes, and (4) the levels of decision maker's inconsistency.

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