Project management decisions with multiple fuzzy goals

In real‐world situations, the project managers must handle conflicting goals that govern the use of the resources within organizations. These conflicting goals must are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The multiple fuzzy goals programming model proposed herein helps project managers to minimize project total costs, total completion time, and total crashing costs considering direct costs, indirect costs, contractual penalty costs, duration of activities and total budget constraint. A numerical example illustrates the feasibility of applying the proposed model to a project management decision problem. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with determined multiple fuzzy goals values. Moreover, the proposed model effectively provides a systematic decision‐making framework, enabling a decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model from the other models include flexible decision‐making processes, multiple objective functions, and wide‐ranging decision information.     

Lane width‐based cellular automata model for mixed bicycle traffic flow

In this paper, an improved extended Burgers cellular automata (EBCA) model for heterogeneous bicycle traffic flow is proposed. The compressibility of bicycle traffic flow is considered as a probability, which is related to the bicycle path width. The proposed improved EBCA model is calibrated and validated using the field data collected from three sites in Hangzhou, China. The proposed model is compared with the original EBCA model that does not consider compressibility. The comparison results show that our improved model can simulate heterogeneous bicycle traffic flow better. Moreover, the proposed model overcomes the shortcoming of the other BCA models that only specific path widths can be simulated directly when lane width is determined. Lastly, the EBCA model performance in the congested regions is improved significantly.     

循环载荷作用下岩石单轴压缩破坏过程的平面弹塑性细胞自动机模型

采用平面弹塑性细胞自动机模型在细观尺度上模拟应变软化岩石类材料的单轴压缩破坏过程。在平面弹性力学细胞自动机的基础上,推导分析平面弹塑性问题的细胞自动机更新规则,开发二维岩石弹塑性细胞自动机数值模拟软件;模拟不同均质度岩石的单轴压缩破坏过程,并在应力峰值后区考虑反复加卸载过程。模拟得到的岩石单轴压缩条件下的全程应力-应变曲线与典型的加卸载应力-应变试验曲线吻合较好,模拟得到的声发射曲线很好地反映出岩石声发射的Kaiser效应。     

Passing Rates to Measure Relaxation and Impact of Lane‐Changing in Congestion

Abstract: Passing rate measurements of backward‐moving kinematic waves in congestion are applied to quantify two traffic features; a relaxation phenomenon of vehicle lane‐changing and impact of lane‐changing in traffic streams after the relaxation process is complete. The relaxation phenomenon occurs when either a lane‐changer or its immediate follower accepts a short spacing upon insertion and gradually resumes a larger spacing. A simple existing model describes this process with few observable parameters. In this study, the existing model is reformulated to estimate its parameter using passing rate measurements. Calibration results based on vehicle trajectories from two freeway locations indicate that the revised relaxation model matches the observation well. The results also indicate that the relaxation occurs in about 15 seconds and that the shoulder lane exhibits a longer relaxation duration. The passing rate measurements were also employed to quantify the postrelaxation impact of multiple lane‐changing maneuvers within a platoon of 10 or more vehicles in queued traffic stream. The analysis of the same data sets shows that lane‐changing activities do not induce a long‐term change in traffic states; traffic streams are perturbed temporarily by lane‐changing maneuvers but return to the initial states after relaxations.     

模拟三点弯曲试验的细胞自动机模型

细胞自动机是一种在随机初始条件下,通过构造简单的数学规则,来描述离散动力系统内部因局部单元之间强烈的非线性作用而导致系统整体自组织演化过程的一种数学模型.在此基础上,以力、位移作为基本状态变量,基于基本的力学规律构造了细胞自动机模型的矢量局部更新规则,建立了一种模拟岩石破坏过程的细胞自动机模型,并克服了以往规则确定随意性以及标量化的缺点.利用该模型模拟了三点弯曲梁的破坏过程,分析了预制裂纹对三点弯曲梁的破坏过程的影响,给出了与破坏过程所对应的应力-应变曲线以及声发射曲线.     

Time–cost optimization: using GA and fuzzy sets theory for uncertainties in cost

Uncertainties should be considered in any time–cost trade‐off problems when minimizing project cost and duration, which leads to the so‐called stochastic time–cost trade‐off problem. A new approach to investigate stochastic time–cost trade‐off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop a solution to the multi‐objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non‐dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision‐making process by selecting specified risk levels and employing the associated Pareto front.     

Fuzzy adaptive decision making model for selection balanced risk allocation

The unbalanced allocation of risks among the contracting parties is an important decision leading to increase of the total cost of a specific project and affects the overall relationship between the contracting parties. Due to common risk allocation decision-making process is based on experiential knowledge, is subjective and implicit. This paper presents a fuzzy adaptive decision making model for selection of balanced risk allocation which transforms the linguistic principles and experiential expert knowledge into a more usable and systematic quantitative-based analysis by using the fuzzy logic. The objectives of balanced risk allocation are developed based on the concept of Competence-Tendency trade-off. The proposed model integrates fuzzy logic qualitative approach and analytic hierarchy process (AHP) adaptive capabilities to evaluate allocation of project risks and determine best party to bear each one. Results from this model show its high capability in addressing most proper risk allocation with least contingency applied to the owner.     

基于FG-MCGDM的水利工程施工进度方案优化

针对水利工程施工进度的多准则群决策问题,提出了一种新的模糊灰色多准则决策模型。该模型基于模糊集理论、灰色关联分析和折衷解的理论方法,将各决策属性和决策者权重的语言变量转化为梯形模糊数;采用改进的 GRA-VIKOR方法对模糊信息群体决策问题进行求解,并对各决策者的群体效益值和个体遗憾值进行聚合;通过折衷解对施工进度方案进行排序,获得最优方案。该模型有效地避免了信息的扭曲和丢失,确保了决策信息的完备性。通过在某水利工程施工进度方案优选的案例分析与计算,证明了该模型的有效性和实用性。     

基于元胞自动机模型的长沙市城市增长模拟研究

元胞自动机具有模拟二维空间演化过程的能力,并且在时间上也是离散的,因此具有很强的时空动态性,它的这种特性使其模拟城市增长具有明显的优势。SLEUTH模型是元胞自动机模型的一种具体实现形式,本文介绍了该模型的具体参数、转换规则以及校正过程,基于GIS方法和遥感数据源,利用该模型重建了长沙市1996～2005年城市增长过程,并结合情景模拟方法预测了2010年长沙市城市空间形态。结果表明,运用SLEUTH模型模拟城市增长是可行的,并且其模拟精度是可以接受的。     

Modeling Risk Allocation in Privately Financed Infrastructure Projects Using Fuzzy Logic

Abstract:   Risk allocation (RA) plays a critical role in privately financed infrastructure projects. Project performance is contingent on whether the adopted RA strategy is efficient. However, no mechanism was specifically designed to facilitate the risk allocation decision-making (RADM) process. Two theoretical frameworks based on the transaction cost economics (TCE) theory and on both the TCE and the resource-based view (RBV) of organizational capability, respectively, were thus adopted in this article. As conventional modeling techniques are not suitable for modeling RADM processes, which involve ambiguous and qualitative information, fuzzy inference systems (FISs) were developed, illustrated, and evaluated to model these frameworks. An industry-wide survey and rounds of expert consultation were conducted to collect data and generate fuzzy rules. It was found that both FISs are capable of reliably explaining the RADM process. In particular, the FIS based on both the TCE and the RBV theories performed more accurately and thus is more suitable for forecasting efficient risk allocation strategy.     

Multicriteria Fuzzy Analysis for a GIS‐Based Management of Earthquake Scenarios

Objective of this article is the formulation and the implementation of a decision‐making model for the optimal management of emergencies. It is based on the accurate definition of possible scenarios resulting from prediction and prevention strategies and explicitly takes into account the subjectivity of the judgments of preference. To this end, a multicriteria decision model, based on fuzzy logic, has been implemented in a user‐friendly geographical information system (GIS) platform so as to allow for the automation of choice processes between several alternatives for the spatial location of the investigated scenarios. In particular, we have analyzed the potentialities of the proposed approach in terms of seismic risk reduction, simplifying the decision process leading to the actions to be taken from directors and managers of coordination services. Due to the large number of variables involved in the decision process, it has been proposed a particularly flexible and streamlined method in which the damage scenarios, based on the vulnerability of the territory, have represented the input data to derive a vector of weights to be assigned to different decision alternatives. As an application of the proposed approach, the seismic damage scenario of a region of 400 km², hit by the 2009 earthquake in L'Aquila (Italy), has been analyzed.     

Decision‐making in a model‐based design process

Decisions early in the design process have a big impact on the life cycle performance of a building. The outcome of a construction project can be improved if different design options can rapidly be analysed to assist the client and design team in making informed decisions in the design process. A model‐based design approach can facilitate the decision‐making process if the design alternatives' performances can be evaluated and compared. A decision‐making framework using a performance‐based design process in the early design phase is proposed. It is developed to support decision‐makers to take informed decisions regarding the life cycle performance of a building. A scenario is developed in order to demonstrate the proposed framework of evaluating the different design alternatives' energy performance. The framework is applicable to decision‐making in a structured design process, where design alternatives consisting of both objective and subjective evaluation criteria can be evaluated.     

岩体破坏演化的物理细胞自动机(PCA)(Ⅰ)——基本模型

根据岩体的结构与破坏特征，建立了一种新的细胞自动机－－二维物理细胞自动机（PCA）的基本模型，由于该模型考虑了岩体材料的非均质性，非连续性和各向异性等特征，因此，可以有效地模拟岩体的破坏过程，该模型对进一步研究岩体的非线性特征具有重要的应用价值。     

空间网格结构优化设计的模糊判决方法研究

在空间网格结构的优化设计过程中,必然会遇到大量的不确定性信息和因素,而且往往要考虑多个目标函数,而各个目标之间存在矛盾及各目标的解具有冲突性,多目标优化问题要求各个目标函数都达到最优一般很难．本在经典模糊判决法的基础上,提出了四种改进的模糊判决法,并利用隶属函数建立模糊优化数学模型转化为非模糊的单目标优化模型,从而可以使用普通优化程序得到模糊优化解．最后,通过二十五杆塔架的数值例题来说明本方法的求解过程并验证了其模糊判决方法的有效性和可行性．     

The impact of interactions in spatial simulation of the dynamics of urban sprawl

This study investigated the modeling process for simulating the spatial dynamics of an urban ecosystem. Logistic regression is a common method for empirically modeling and analyzing land use and land use change. In most conventional applications of logistic regression, only the individual factors of the system are considered in the development of the logistic regression functions. However, this does not consider the relationships among factors that potentially occur within most ecosystems. Factors in a system, especially an urban system, are usually not fixed and not independent of each other, but rather are influenced by each other. Based on this point of view, the interactions of factors are introduced into a logistic regression in this study. This technique has been tested with a case study using historical land use maps and a spatially explicit dynamic cellular automata urban sprawl model. Using historical land use data, a logistic regression was used to analytically weight the scores of the driving factors of an urban sprawl model for predicting probability maps of land use change. The results of the case study have verified that interactions of factors can significantly improve the prediction of spatial dynamics of urban sprawl, and can provide a means to improve cellular automata models for simulation of the dynamics of urban and other ecosystems.     

Two‐Dimensional Simulation of Turning Behavior in Potential Conflict Area of Mixed‐Flow Intersections

The potential conflict area of intersection is the space where conflicting traffic flows pass through in the same signal phase. At this area, turning vehicles interact with most traffic flows, which introduce complex features including variation of trajectories and shared‐priority phenomenon. The traditional one‐dimensional simulation oversimplifies these features with lane‐based assumption. This study integrates the modified social force model with behavior decision and movement constraints to reproduce the two‐dimensional turning process. The method is framed into a three‐layered mathematical model. First, the decision layer dynamically makes decision for turning patterns. Then the operation layer uses the modified social force model to initially generate vehicle movements. Finally, the constraint layer modifies the vehicular motion with vehicle dynamics constraints, boundary of intersection and the collision avoidance rule. The proposed model is validated using trajectories of left‐turn vehicles at a real‐world mixed‐flow intersection with nonprotected signal phases, resulting in a more realistic simulation than previous methods. The distributions of decision points and travel time in simulation are compared with the empirical data in statistics. Moreover, the spatial distribution of simulated trajectories is also satisfactory.     

Bridge Condition Rating Using an Eigenvector of Priority Settings

Abstract: To circumvent possible inconsistencies in inspection and rating of highway bridges, two models based on fuzzy logic have been proposed in the literature. These models combine the condition rating of the various elements of the main bridge components to evaluate the overall condition of these components. The first method uses fuzzy weighted average, and the second uses the fuzzy computational technique known as resolution identity of fuzzy sets. A third model proposed by the authors and implemented in a knowledge-based expert system environment is presented in detail. The fuzzy inference model is based on a priority setting obtained through the solution of an eigenvector problem involving a pairwise comparison matrix of importance. This method and the associated solution technique were developed originally for general use in multiattribute decision making but were never used in a bridge engineering application. The proposed model is superior to other models for bridge rating previously developed because it provides priority settings of the individual elements of a bridge component in addition to the final rating of that component. The computer program was tested using actual bridge inspection data.     

A Support System for Fuzzy Optimum Aseismic Structural Design of Reinforced Concrete Buildings Using Graphical Representation

Abstract: In this paper, a support system of optimum aseismic design is proposed on the basis of fuzzy set theory and a graphical representation method. In optimum aseismic design of buildings, it is necessary to take account of subjective evaluation of users. In this system, a hierarchical model is employed to idealize and model the decision process of optimum aseismic design. By applying fuzzy set theory, this system can take account of subjective evaluation of users. The system is a prototype of an expert system for optimum aseismic design, and its knowledge is compiled interactively as numerical values by the fuzzy confluence rule and membership functions in fuzzy set theory in accordance with the hierarchical model given by users. Knowledge, which is necessary to perform the inference on optimum aseismic design, is acquired interactively. Optimization is performed by fuzzy multiobjective maximizing decision, and the maximum evaluation values of the top attribute can be found. Furthermore, distributions of the grade of membership value in maximizing the decision process are graphically represented, so the user can understand this process easily and intuitively. A case study is carried out for a reinforced concrete typical high school building in Kobe City.     

Integrating a Human Behavior Model within an Agent‐Based Approach for Blasting Evacuation

Several studies on Emergency Management are available in the literature, but most of them do not consider how the human behavior during an emergency can affect the evacuation process. Therefore, the novel contribution of this article is the implementation of an agent‐based model to describe the evacuation, due to a blast in a public area, integrated with a human behavior analytical model. Each agent has its own behavior that is described in a layered framework. The first layer simulates the “agent's features” function. Then, an “individual module” describes dynamically the emotional aspects using (i) the Decision Field Theory, (ii) a stationary stochastic model, and (iii) the results coming from a questionnaire. An agent‐based model with integrated human behavior is proposed to test critical infrastructures in emergency conditions without performing full scale evacuation tests. Analyses could be performed both in real time with a hazard scenario and at the design level to predict the system response to identify the optimal configuration. Therefore, the development of the proposed methodology could support both designers and policy makers in the decision‐making process.     

Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects

The undertaking of construction projects in metropolitan areas is a risky, competitive, and dynamic proposition requiring a reliable risk assessment model for adequate planning. This study employs a fuzzy multiple criteria decision making (FMCDM) approach to systematically assess risk for a metropolitan construction project. Consistent fuzzy preference relations (CFPR) are used to measure and investigate the relative impact on project performance of twenty identified risk factors included in four risk dimensions. The fuzzy multiple attributes direct rating (FMADR) approach is employed to analyze the occurrence probability of multiple risk factors. Furthermore, the level of risk for the overall project caused by individual risk factor is evaluated with the synthesized analysis of the relative impacts and probability of occurrence. The implementation of FMCDM makes the proposed risk assessment approach more reliable and practical than the traditional statistical approach. The proposed approach can be employed to effectively evaluate the overall project risk, and can be benefited to efficiently identify significant risks of a metropolitan construction project.