A management oriented approach to reduce a project duration and its risk (variability)

The effects of different activities on risk and the expected completion time of a project are not the same; various activities have various effects on the successful completion of a project. Based on this fact, one of the most important issues in project management is to determine important activities and the amount of effort that should be assigned to control them, thereby completing the project successfully. In this paper, one index and one method are proposed to satisfy this necessity. Our main hypothesis is, expending effort on activities and controlling them actively results in activities risk reduction. Based on this hypothesis, the proposed index and method are compared to existing indices in the literature. Comparison results show that the proposed index and method strongly surpass other indices.     

A novel two-phase group decision making approach for construction project selection in a fuzzy environment

This paper considers a construction project problem under multiple criteria in a fuzzy environment and proposes a new two-phase group decision making (GDM) approach. This approach integrates a modified analytic network process (ANP) and an improved compromise ranking method, known as VIKOR. To take uncertainty and risk into account, a new decision making approach is presented with multiple fuzzy information by a group of experts, and a risk attitude for each expert is incorporated that can be expressed linguistically. First, a modified fuzzy ANP method is introduced to address the problem of dependence as well as feedback among conflicting criteria and to determine their relative importance. Then, a fuzzy VIKOR method is extended to rank potential projects on the basis of their overall performance. An illustrative example from the literature is provided for the construction project problem to demonstrate the effectiveness and feasibility of the proposed approach. The computational results show that the proposed two-phase GDM approach is suitable to cope with imprecision and subjectivity for the complicated decision making problem. Finally, the associated results of the proposed approach with risk attitudes and without risk attitudes are compared with the results reported by Cheng and Li [1], and the merits are highlighted.     

基于合作的工程项目风险模糊评价新方法

工程项目的目标风险包括工期风险、费用风险、质量风险、安全风险和环境风险,研究已经表明,同一风险因素会同时对不同的目标产生影响.另外,工程项目管理各方在进行目标管理过程中的合作性也会对目标的最终完成产生影响.因此,将同一风险因素对不同目标的影响以不同的权重表示,并将项目管理各方的合作性作为目标风险的影响因素引入到风险评价中,利用模糊推理的方法建立了基于合作的工程项目风险评价模型,提出了工程项目风险分析的一种新方法.     

A DST-based approach for construction project risk analysis

Despite its huge potential in risk analysis, the Dempster–Shafer Theory of Evidence (DST) has not received enough attention in construction management. This paper presents a DST-based approach for structuring personal experience and professional judgment when assessing construction project risk. DST was innovatively used to tackle the problem of lacking sufficient information through enabling analysts to provide incomplete assessments. Risk cost is used as a common scale for measuring risk impact on the various project objectives, and the Evidential Reasoning algorithm is suggested as a novel alternative for aggregating individual assessments. A spreadsheet-based decision support system (DSS) was devised to facilitate the proposed approach. Four case studies were conducted to examine the approach's viability. Senior managers in four British construction companies tried the DSS and gave very promising feedback. The paper concludes that the proposed methodology may contribute to bridging the gap between theory and practice of construction risk assessment.     

Cost impact of float loss on a project with adjustable activity durations

Although delays to non-critical activities within the float do not always affect the overall completion time of a project, they commonly cause disputes over the impact cost and apportionment resulting from the complexity of resource utilization in construction projects. Therefore, considerable attention has been focused on providing an effective and reliable method for analysing the effects of float loss. Several recent studies have proposed various methods; however, most of these methods are based on the assumption of a fixed duration for each activity or activity-based cost simulation. Few studies have considered the trade-off between time and costs and the integration of project resources. Using genetic algorithms, this study introduces a critical path method (CPM)-modified resource-integrated optimization model and successfully quantifies the impact of float loss on the total cost of the project. The results provide objective quantification for accurately evaluating the impact of within-float delays and facilitate the analysis of the impact of delay claims on cost and apportionment in construction projects.     

A hierarchical copula-based world-wide valuation of sovereign risk

We propose a new model for the aggregation of risks that is very flexible and useful in high dimensional problems. We propose a copula-based model that is both hierarchical and hybrid (HYC for short), because: (i) the dependence structure is modeled as a hierarchical copula, (ii) it unifies the idea of the clusterized homogeneous copula-based approach (CHC for short) and its limiting version (LHC for short) proposed in Bernardi and Romagnoli (2012, 2013). Based on this, we compute the loss function of a world-wide sovereign debt portfolio which accounts for a systemic dependence of all countries, in line with a global valuation of financial risks. Our approach enables us to take into account the non-exchangeable behavior of a sovereign debts’ portfolio clustered into several classes with homogeneous risk and to recover a possible risks’ hierarchy. A comparison between the HYC loss surface and those computed through a pure limiting approach, which is commonly used in high dimensional problems, is presented and the impact of the concentration and the granularity errors is appreciated. Finally the impact of an enlargement of the dependence structure is discussed, in the contest of a geographical area sub-portfolios analysis now relevant to determine the risk contributions of subgroups under the presence of a wider dependence structure. This argument is presented in relation to the evaluation of the insurance premium and the collateral related to the designed project of an euro-insurance-bond.     

Multiobjective Q-analysis with concordance and discordance concepts

A multicriterion decision-making (MCDM) technique with possibly nonnumerical criteria, called Multicriteria Q-Analysis I (MCQA-I), developed earlier on the basis of only a concordance analysis, is extended to include a measure of discordance. This new version, labeled MCQA-II, reduces an MCDM problem to the tradeoff between three conflicting indices calculated for each project or alternative. The indices are respectively a value or utility-type index PSI, and two outranking-type indices PCI and PDI. The example of selecting a project to alleviate pollution problems in the lower San Francisco Bay area illustrates the application of both versions of MCQA. A sensitivity analysis performed on the slicing-level set tends to show that MCQA-II leads to a more stable ranking than MCQA-I; in either case, application of the technique leads to selection of the project preferred in practice.     

基于模糊数整体和局部特征的一种新排序方法

利用反映模糊数整体和局部特征的三个重要指标:模糊数的均值,截集的中点和扩展,本文提出一种新的模糊数排序方法.该方法将每个模糊数独立地映射到实数轴上,得到一个以数字大小为基准的自然顺序,不仅体现决策者对各排序指标的偏好,而且无需对模糊数进行两两比较,计算简便,易于理解,尤其是对三角和梯形模糊数而言,数值实验表明该方法在一定程度上克服了已有方法的缺陷.     

Impact of insurance for operational risk: Is it worthwhile to insure or be insured for severe losses?

Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach allows a provision for reduction of capital as a result of insurance mitigation of up to 20%. This paper studies different insurance policies in the context of capital reduction for a range of extreme loss models and insurance policy scenarios in a multi-period, multiple risk setting. A Loss Distributional Approach (LDA) for modeling of the annual loss process, involving homogeneous compound Poisson processes for the annual losses, with heavy-tailed severity models comprised of α-stable severities is considered. There has been little analysis of such models to date and it is believed insurance models will play more of a role in OpRisk mitigation and capital reduction in future. The first question of interest is when would it be equitable for a bank or financial institution to purchase insurance for heavy-tailed OpRisk losses under different insurance policy scenarios? The second question pertains to Solvency II and addresses quantification of insurer capital for such operational risk scenarios. Considering fundamental insurance policies available, in several two risk scenarios, we can provide both analytic results and extensive simulation studies of insurance mitigation for important basic policies, the intention being to address questions related to VaR reduction under Basel II, SCR under Solvency II and fair insurance premiums in OpRisk for different extreme loss scenarios. In the process we provide closed-form solutions for the distribution of loss processes and claims processes in an LDA structure as well as closed-form analytic solutions for the Expected Shortfall, SCR and MCR under Basel II and Solvency II. We also provide closed-form analytic solutions for the annual loss distribution of multiple risks including insurance mitigation.     

A confidence voting process for ranking problems based on support vector machines

In this paper, we deal with ranking problems arising from various data mining applications where the major task is to train a rank-prediction model to assign every instance a rank. We first discuss the merits and potential disadvantages of two existing popular approaches for ranking problems: the ‘Max-Wins’ voting process based on multi-class support vector machines (SVMs) and the model based on multi-criteria decision making. We then propose a confidence voting process for ranking problems based on SVMs, which can be viewed as a combination of the SVM approach and the multi-criteria decision making model. Promising numerical experiments based on the new model are reported. The research of the last author was supported by the grant #R.PG 0048923 of NESERC, the MITACS project “New Interior Point Methods and Software for Convex Conic-Linear Optimization and Their Application to Solve VLSI Circuit Layout Problems” and the Canada Researcher Chair Program.     

项目网络中考虑支配与扩散关系的组合决策

单纯侧重项目自身属性而不考虑项目关联性以及由项目衍生而来的技术、经验/信息扩散对项目组合决策时的影响,易导致决策偏差,低估具有潜在技术先导性项目的价值。对此,引用复杂网络理论,以项目关联性的视角,将项目间支配和扩散关系分别抽象为有向加权网络,运用K-shell分解方法构建项目组合网络中基于支配关系的项目影响力模型以及技术、经验/信息在项目间扩散传播的模型。然后,基于PageRank算法,综合考虑项目间支配与扩散关系,建立了项目优先级排序决策模型。最后,通过算例分析说明了该模型与算法的可行性与有效性,为企业项目组合决策提供了有益的参考。     

The degree ratio ranking method for directed graphs

One of the most famous ranking methods for digraphs is the ranking by Copeland score. The Copeland score of a node in a digraph is the difference between its outdegree (i.e. its number of outgoing arcs) and its indegree (i.e. its number of ingoing arcs). In the ranking by Copeland score, a node is ranked higher, the higher is its Copeland score. In this paper, we deal with an alternative method to rank nodes according to their out- and indegree, namely ranking the nodes according to their degree ratio, i.e. the outdegree divided by the indegree. To avoid dividing by zero, we add 1 to both the out- as well as indegree of every node. We provide an axiomatization of the ranking by degree ratio using a clone property, which says that the entrance of a clone or a copy (i.e. a node that is in some sense similar to the original node) does not change the ranking among the original nodes. We also provide a new axiomatization of the ranking by Copeland score using the same axioms except that this method satisfies a different clone property. Finally, we modify the ranking by degree ratio by taking only the out- and indegree, but by definition assume nodes with indegree zero to be ranked higher than nodes with positive indegree. We provide an axiomatization of this ranking method using yet another clone property and a maximal property. In this way, we can compare the three ranking methods by their clone property.     

A new method for complete ranking of DMUs

So far numerous models have been proposed for ranking the efficient decision-making units (DMUs) in data envelopment analysis (DEA). But, the most shortcoming of these models is their two-stage orientation. That is, firstly we have to find efficient DMUs and then rank them. Another flaw of some of these models, like AP-model (A procedure for ranking efficient units in data envelopment analysis, Management Science, 39 (10) (1993) 1261–1264), is existence of a non-Archimedean number in their objective function. Besides, when there is more than one weak efficient unit (or non-extreme efficient unit) these models could not rank DMUs. In this paper, we employ hyperplanes of the production possibility set (PPS) and propose a new method for complete ranking of DMUs in DEA. The proposed approach is a one stage method which ranks all DMUs (efficient and inefficient). In addition to ranking, the proposed method determines the type of efficiency for each DMU, simultaneously. Numerical examples are given to show applicability of the proposed method.     

Modelling and assessing ERP project risks: A Petri Net approach

Risk management of Enterprise Resource Planning (ERP) projects is largely recognized as a very complex task both by academics and practitioners. Strict interconnections among risk factors often occur so that indirect effects on the overall project performance are very likely. Unfortunately, the implications of interdependency are usually underestimated by project managers and decision makers since they are difficult to include in any risk assessment logic. This work shows how Colored Petri Nets (CPNs) can be used to model risk factors in ERP projects in order to deal with the problem of interdependence in risk assessment. The technique is presented through an application to a real case study. Findings highlight the importance of interdependence and the indirect links for an effective ranking of risks. Furthermore, results emphasize the valuable support of CPNs in risk factor modelling since they allow both a more structured and systematic risk analysis and a more accurate planning for effective risk treatment actions.     

Aggregation of ordinal data using ordered weighted averaging operator weights

In multi-criteria decision-making problems, ordinal data themselves provide a convenient instrument for articulating preferences but they impose some difficulty on the aggregation process since ambiguity prevails in the preference structure inherent in the ordinal data. One of the key concerns in the aggregation of ordinal data is to differentiate among the rank positions by reflecting decision-maker??s preferences. Since individual attitude is fairly different, it is presumable that each ranking position has different importance. In other words, the quantification schemes among the rank positions could vary depending on the individual preference structure. We find that, among others, the ordered weighted averaging (OWA) operator can help to take this concept into effect on several reasons. First, the OWA operator provides a means to take into account a discriminating factor by introducing the measure of attitudinal character. Second, it can produce appropriate ranking weights corresponding to each rank position by solving a mathematical program subject to the constraint of attitudinal character. To better understand the attitudinal character playing a role as a discriminating factor, we develop centered ranking weights from ordinal weak relations among the ranking positions and then investigate their properties to relate them with the OWA operator weights having the maximum entropy. Finally, we present a method for generating the OWA operator weights via rank-based weighting functions.     

Using a risk-based approach to project scheduling: A case illustration from semiconductor manufacturing

This paper introduces a risk-based optimization method to schedule projects. The method uses risk mitigation and optimal control techniques to minimize variables such as the project duration or the cost estimate at completion. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to determine the set of mitigation actions to be executed and the time in which they are taken. A real-life project in the field of semiconductor manufacturing has been taken as an example to show the benefits of the method in a deterministic case and a Monte Carlo simulation has also been carried out.     

RM approach for ranking of generalized trapezoidal fuzzy numbers

Ranking of fuzzy numbers play an important role in decision making, optimization and 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 (3): 6833) is incorrect. The main aim of this paper is to propose a new approach for the ranking of generalized trapezoidal fuzzy numbers. The proposed ranking approach is based on rank and mode so it is named as an RM approach. The main advantage of the proposed approach is that the proposed approach provides 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 (3): 375).     

Efficacy of traditional sport tournament structures

The ranking abilities of some traditional sport tournaments under a variety of initial conditions were analyzed using Monte Carlo procedures. A range of outcome measures were used since a tournament’s efficacy will likely depend upon both its objectives and the playing abilities of its contestants. The traditional knockout (KO) is a weak tournament in its ability to rank all players although it requires fewer games than the round robin (RR). The KO tournament’s efficacy is notably enhanced, however, in some cases beyond that of the RR tournament if double elimination procedures are used and the seeding is reasonably accurate. Under these conditions, we consider the KO structure to be the best available structure for most tournament purposes. A secondary recommendation of this study is that the fourth and fifth placings be reversed in the traditional KO structures for ranking all players in the eight player situation.     

地方政府债券信用风险缓释工具定价研究

随着地方政府债券发行规模的扩大,地方政府债务的信用风险日益凸出。本研究以企业债信用风险缓释工具的推出为契机,借鉴结构化模型的思路和KMV模型求解违约概率的逻辑,通过Monte Carlo方法模拟地方政府的违约过程,直接测算地方政府的整体违约概率;结合简约化模型的思路测算地方政府债券的具体违约概率,计算信用风险缓释工具的理论价格,从而构建了地方政府债券信用风险缓释工具的混合定价模型。研究发现,以企业债券为标的测算出的模型理论价格与市场报价基本一致,参数的敏感性检验进一步验证了模型的理论自洽性和实证可靠性。上述结论或将为新《预算法》实施过程中地方政府债务的治理与掌控及中国区域性、系统性金融风险的防范提供新思路。     

A new approach to find project characteristics and multiple possible critical paths in a fuzzy project network

Graphs are widely used to represent data and relationships. Among all graphs, a particularly useful family is the family of trees. In this paper, we utilize a rooted tree to describe a fuzzy project network as it enables simplification in finding earliest starting times and trapezoidal fuzzy numbers to express the operation times for all activities in project network. As there is an increasing demand that the decision maker needs “Multiple possible critical paths” to decrease the decision risk for project management, in this paper, we introduce an effective graphical method to compute project characteristics such as total float, earliest and latest times of activities in fuzzy project network and a new ranking to find possible critical paths. Numerical example is provided to explain the proposed procedure in detail; the results have shown that the procedure is very useful and flexible in finding total floats. By comparing the critical paths obtained by this method with the previous methods, it is shown that the proposed method is effective in finding possible critical paths.