R&D project selection using the analytic network process

The analytic network process (ANP) is presented as a potentially valuable method to support the selection of projects in a research and development (R&D) environment. This paper first discusses the requirements of the R&D project selection problem, which requires the allocation of resources to a set of competing and often disparate project proposals. Among the factors complicating this task is the need to make the decision within the framework of an enterprise's strategic objectives and organizational structure while considering and integrating financial and strategic benefits of each project. The paper discusses the use of the ANP, a general form of Saaty's analytic hierarchy process, as a model to evaluate the value of competing R&D project proposals. A generic ANP model developed by the authors, which includes in its decision levels the actors involved in the decision, the stages of research, categories of metrics, and individual metrics, is presented. The paper concludes with a case study describing the implementation of this model at a small high-tech company, including data based on the actual use of the decision making model     

Managing technology development for safety-critical systems

This paper presents a model that determines the optimal budget allocation strategy for the development of new technologies, for safety-critical systems, over multiple decision periods. The case of the development of a hypersonic passenger airplane is used as an illustration. The model takes into account both the probability of technology development success as a function of the allocated budget and the probability of operational performance of the final system. It assumes that the strategy is to consider (and possibly fund) several approaches to the development of each technology to maximize the probability of development success. The model, thus, decomposes the system's development process into multiple technology development modules (one for each technology needed), each involving a number of alternative projects. There is a tradeoff between development speed and operational reliability when the budget must be allocated among alternative technology projects with different probabilities of development success and operational reliability (e.g., an easily and quickly developed technology may have little robustness). The probabilities of development and operational failures are balanced by a risk analysis approach, which allows the decision maker to optimize the budget allocation among different projects in the development program, at the beginning of each budget period. The model indicates that by considering reliability in the R&D management process, the decision maker can make better decisions, optimizing the balance between development time, cost, and robustness of safety-critical systems.     

Project Acceleration via Activity Crashing, Overlapping, and Substitution

It is an established fact that projects are almost always behind schedule. Consequently, there is a great need for the allocation of additional resources with a view to accelerating projects, so as to ensure delivery on the planned date. These resources are obtained from project budget contingency, whose purpose is to foresee and budget for delays arising from disruptions, inaccurate activity time and cost estimates, and resource nonavailability when required for the execution of project activities. This type of problem arises both in the planning phase of a project, particularly in the context of bidding, as well as in ongoing projects, including new product development projects. The research reported in this paper provides a mixed-integer nonlinear programming model for the acceleration of projects, employing the simultaneous crashing, overlapping, and substitution of project activities. In order to ensure convergence, this model is transformed exactly into a mixed-integer linear programming model. The assumptions of the model are presented and discussed with engineering project management practice in mind. Application of the model to four examples of different sizes and nature, three of which are practical cases, demonstrates the efficiency of the model, implemented in commercial optimization software, in solving practical project acceleration problems.      

Calculation of contingency in construction projects

This paper presents a probabilistic model that considers the random nature of change orders and their impact on the cost and schedule of a construction project. The model incorporates uncertainties in project cost and schedule and calculates the contingency based on the level of confidence specified by the owner. It assumes a Poisson arrival pattern for change orders in a construction project. The effect of schedule delays in further increasing the project cost is considered explicitly and the effect of correlation between change orders is discussed and analytically considered. The proposed model may be used for budgeting purposes at the early stages of project development. Typical applications of the proposed model in the context of construction industry are discussed. A numerical example is presented that demonstrates the use of the model in establishing a budget contingency. The results of the example are compared with actual data from previous construction projects.     

R&D project selection

The research and development project selection decision is concerned with the allocation of resources to a set of proposals for scientific and engineering activities. The project selection process can be viewed as a multiple-criteria decision-making problem, within the context of the long-range and strategic planning process of the firm. The purpose of this paper is explore the applicability of several approaches, including the Analytic Hierarchy Process, for priority setting and resource allocation in the industrial R&D environment. The incorporation of these models into expert support systems for R&D project selection is discussed.     

Multiobjective water resources investment planning under budgetaryand socio-technical uncertainties

An integration of stochastic dynamic programming (SDP) and integer goal programming (IGP) modeling framework is proposed to handle problems of multiobjective-multicriteria sequential decision making under budgetary and socio-technical uncertainties inherent in water resources investment planning. In the proposed SDP model, probabilities of the funding levels in any time period that are generated using a subjective model are employed to handle budgetary fluctuations. This subjective model consists of historical data as a basic rate, functional relationships among inter-related parameters of the SDP model, scenarios of future budget availability, and subjective inputs elicited from a group of decision makers through a collective opinion technique. Application of the SDP model primarily yields an optimal investment planning policy that recognizes the possibility that actual funding received maybe less than that anticipated, and therefore the projects being implemented under the anticipated budget would be interrupted. In this integrated model, economic return of each level of investment decision together with its associated project portfolio is determined by the IGP model based on goals and criteria preferences with explicit consideration to socio-technical uncertainty     

Managing Test-Procedures to Achieve Reliable Software

Quantitative decision-making procedures are proposed to aid software project managers to manage effectively the testing stage during software project development. The module and integration testing phases are thoroughly investigated. Decision procedures which maximize the reliability and/or minimize some cost-benefit objective subject to a time and/or budget constraint are suggested. These procedures optimally allocate test time to the modules for module testing and select the optimal data mixture for integration testing. Testing of computer software is a major component of the software development effort. An efficient allocation of computer time among various modules during testing can appreciably improve reliability and shorten the testing stage. Using decision models presented in this paper, a project manager can effectively allocate test time during module testing and select the best data mixture for integration testing. The models are based upon software failure data that are collected during testing. These decision models can be valuable not only for the project manager but for the group responsible for generating the appropriate test data.     

A specific decision support system (SDSS) to develop an optimalproject portfolio mix under uncertainty

A specific decision support system (SDSS) than can be used as a methodology for choosing an optimal portfolio mix of information systems projects is described. The SDSS is developed by applying a number of well-known management science techniques. A net present value (NPV) of the projects is maximized within limited resources, and the solution of the model provides the optimal project start period, system development language, and staff size. The SDSS conducts a risk analysis on those variables that are deemed critical when determining the optimal solution. The final phase of the SDSS establishes the value of perfect information on these critical variables. To demonstrate the usefulness of the model an example consisting of five information system (IS) projects is presented. It is shown that, given the estimates of the exogenous parameters of the IS project environment, the model can determine when to begin the project development, which systems development language to use, and the number of systems development staff assign to each project. The degree of the variability of the estimates of exogenous parameters is evaluated through empirical probability distributions     

软件项目风险管理方法探讨

软件项目开发和管理中一直存在着种种不确定性,如需求不确定、技术不确定、人员不确定、管理不确定等,严重影响着项目的进度、成本和质量,以及项目完成和交付。但这些软件风险并未得到充分的重视和系统的研究,本文就中小型软件项目中风险识别、风险分析、风险应对和风险监控的方法进行由浅入深地探讨,并给出了应用实例。     

Factors Which Contribute to Project Management Difficulties in Brazilian Industrial Research Institutes

Many South American industrial research institutes are adopting project management concepts and practices as a means of better meeting the needs of the developing industrial sectors for technical development and assistance services. The traditional role of the researcher responsible solely for technical issues is evolving into that of the engineering manager who is responsible for the attainment of technical goals within the constraints of time schedules and budgets. Interviews were conducted with 24 project leaders drawn from two industrial research institutes located in the state of S?o Paulo, Brazil, to identify the factors which they believe contribute to the difficulty of performing selected project management tasks. The results of the rank ordering of selected tasks is as follows: 1) most difficult performing within schedule; 2) performing within budget; 3) establishing project schedule; 4) establishing budget; 5) securing client funding approval; 6) maintaining competent technical support staff on project; 7) maintaining competent professional staff; 8) defining project technical objectives; 9) attaining technical objectives; and 10) least difficult securing institute approval of project. The factors identified by the leaders as contributing to the relative degree of difficulty of each of the tasks were classified into three groups; those factors which exist within the project team, those which exist within the institute, and those which exist within the environment of the institute. Several factors within the project team were identified as contributing to the relative difficulty of establishing and attaining project schedules and budgets.     

Factors Which Contribute to Project Management Difficulties in Brazilian Industrial Research Institutes

Many South American industrial research institutes are adopting project management concepts and practices as a means of better meeting the needs of the developing industrial sectors for technical development and assistance services. The traditional role of the researcher responsible solely for technical issues is evolving into that of the engineering manager who is responsible for the attainment of technical goals within the constraints of time schedules and budgets. Interviews were conducted with 24 project leaders drawn from two industrial research institutes located in the state of Sao Paulo, Brazil, to identify the factors which they believe contribute to the difficulty of performing selected project management tasks. The results of the rank ordering of selected tasks is as follows: 1) ?most difficult? performing within schedule; 2) performing within budget; 3) establishing project schedule; 4) establishing budget; 5) securing client funding approval; 6) maintaining competent technical support staff on project; 7) maintaining competent professional staff; 8) defining project technical objectives; 9) attaining technical objectives; and 10) ?least difficult? securing institute approval of project. The factors identified by the leaders as contributing to the relative degree of difficulty of each of the tasks were classified into three groups; those factors which exist within the project team, those which exist within the institute, and those which exist within the environment of the institute. Several factors within the project team were identified as contributing to the relative difficulty of establishing and attaining project schedules and budgets.     

V2X offloading and resource allocation under SDN and MEC architecture

To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and software defined network (SDN) was constructed.MEC sinks cloud serviced to the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing.The SDN controller could sense network information from a global perspective,flexibly schedule resources,and control offload traffic.To further reduce the system overhead,a joint task offloading and resource allocation scheme was proposed.By modeling the MEC-based V2X offloading and resource allocation,the optimal offloading decision,communication and computing resource allocation scheme were derived.Considering the NP-hard attribute of the problem,Agglomerative Clustering was used to select the initial offloading node,and Q-learning was used for resource allocation.The offloading decision was modeled as an exact potential game,and the existence of Nash equilibrium was proved by the potential function structure.The simulation results show that,as compared to other mechanisms,the proposed mechanism can effectively reduce the system overhead.     

基于不完美CSI的D2D通信网络鲁棒能效资源分配算法

针对设备到设备(D2D)直连通信网络传统最优资源分配算法在随机信道时延、信道估计误差影响下鲁棒性弱的问题,该文在考虑参数不确定性影响的条件下,提出D2D用户总能效最大的鲁棒资源分配算法。考虑干扰功率门限、用户最小速率需求、最大传输功率和子信道分配约束,建立了下垫式频谱共享模式下多用户D2D网络资源分配模型。基于有界信道不确定性模型,利用最坏准则方法将原非凸鲁棒资源分配问题转换为确定性的凸优化问题。然后利用拉格朗日对偶理论求得资源分配的解析解。仿真结果表明所提出的算法具有很好的鲁棒性。     

基于监督学习的可信云计算资源拍卖机制研究

使用拍卖方式来进行资源分配可以使得资源提供商获得更大的收益,是云计算领域近年来研究的重点之一。但资源分配问题是NP难的,无法在多项式时间内求解,现有研究主要通过近似算法或启发式算法来实现资源分配,但存在算法耗时长,与最优解相比准确度低的缺点。监督学习中分类及回归思想可对多维云资源分配问题进行建模和分析,针对不同问题规模,该文提出基于线性回归、逻辑回归、支持向量机的3种资源分配算法,并且基于临界值理论设计了支付价格算法,从而确保拍卖机制的可信性。在社会福利、分配准确率、算法执行时间、资源利用率等多个方面进行测试分析,取得了很好的效果。     

基于粒子群优化的地震应急物资多目标调度算法

合理高效地优化调度救灾物资对提升地震应急救援效果具有重要意义。地震应急需要同时兼顾时效性、公平性和经济性等相互冲突的多个调度目标。该文对地震应急物资调度问题建立了带约束的3目标优化模型,并设计了基于进化状态评估的自适应多目标粒子群优化算法(AMOPSO/ESE)来求解Pareto最优解集。然后根据“先粗后精”的决策行为模式提出了由兴趣最优解集和邻域最优解集构成的Pareto前沿来辅助决策过程。仿真表明该算法能有效地获得优化调度方案,与其他算法相比,所得Pareto解集在收敛性和多样性上具有性能优势。

     

异构无线网络多链路接入动态资源分配算法

异构无线网络(Heterogeneous Wireless Networks, HWNs)环境下现有接入控制算法的主要问题是通过单一的传输链路建立移动用户和无线网络之间的连接,并且接入过程中的资源分配没有对全网的传输性能进行优化。为了解决上述问题,该文分析了HWNs中的资源分配模型和链路接入速率模型,提出一种支持多链路接入的动态资源分配算法MLA-DRA。算法以最大化系统传输速率为目标,将用户接入过程转化为前后相互联系的多阶段决策过程,利用前一阶段用户的资源分配状态计算下一阶段用户的最优解,从而推导出系统传输速率的最优值。在仿真平台上对MLA-DRA算法进行了性能分析,并且和其它算法进行了性能比较,实验结果表明,MLA-DRA算法能有效利用系统资源以及提高系统传输速率。     

Electric power generation planning for interrelated projects: a real options approach

The market uncertainties in the generation business in the U.S. electric power industry have increased the significance of two factors in generation planning: financial risks and managerial flexibilities. At the same time,numerous utilities have multiple generation planning projects that are interrelated with respect to their market values. For such utilities, in order to quantitatively address these two factors, in this paper, we develop and analyze a real options model for general n interrelated projects. Specifically, first, we derive a unique lattice process that approximates interrelated continuous processes for the evolution of values of projects and options (e.g., selling a constructed project). The steps of the approximation for n projects are presented progressively starting from two projects. Next, based on the lattice process, we investigate the impact of interrelation on the values of options. Then, we provide a backward dynamic programming model for optimal sequential decision making where the decisions are made over the options. Finally, managerial insights and economic implications are illustrated via numerical examples.     

Impact of radio resource allocation policies on the TD-CDMA systemperformance: evaluation of major critical parameters

This paper investigates the impact of major critical parameters and the effect of some radio resource allocation policies on the TD-CDMA system performance. Critical parameters are related either to the user behavior (e.g., user mobility, activity factors) or to processing techniques and algorithms implemented to control network performance and individual radio link quality (e.g., joint detection imperfection, handover margin, timeout for maintaining alive bad radio links). Network topology (e.g., distance between neighboring base stations) also undoubtedly influences capacity results. Analysis is carried out through accurate modeling of user behavior, interference scenarios, and power budget limitations at both terminals and infrastructure, allowing for proper implementation of radio resource allocation algorithms. Among these algorithms, power management (both at the initial channel assignment and during communication), dynamic channel allocation (DCA), and ongoing calls management are explored. An event-driven simulation approach was considered to model realistic system behavior and address system stability under various events generating traffic/interference fluctuations (e.g., call arrivals and departures, handovers, steps of power control loops). Such an approach is expected to offer a good estimate of the real conditions provided the propagation models are close to real life. As a consequence, measures to be taken to avoid/control overloading in a TD-CDMA (CDMA in general) environment can be naturally derived and tested with this methodology     

Project scheduling conflict identification and resolution using genetic algorithms (GA)

Project management has gained a lot of application in software development activity in the past two decades. It is now considered to be one of the most critical component of software development lifecycle. Project management is traditionally defined as the discipline of planning, organizing, and managing activities and resources for successful execution and completion of project goals and objectives. In this respect, project management holds a key position in satisfactory completion of projects. That is the reason that we have a complete knowledge domain we know as software project management (SPM). The main purpose of SPM is to achieve all the project goals and objectives while working within the constraints posed by project environment and stakeholders. These constraints include (but not limited to) time, scope, resources, resource allocation and optimization etc. Successful project planning involved careful selection and synchronization of resources in order to achieve satisfactory completion of projects. These resources include human resource, rime, infrastructure etc. While planning software projects, it is natural to be confronted with various conflicts in resource allocation. It becomes a very time consuming activity to identify and sort out these conflicts when project size is large and time constraints are severe. A good project management activity is one which can effectively foresee these conflicts and resolve them in an optimal fashion. Computationally intelligent techniques are a good candidate to be used for the purpose of automation of this task. In this paper, a genetic algorithm based technique for conflict identification and resolution for project activities has been proposed. The effectiveness and utility of such a technique has also been discussed in this paper. The technique has been subjected to extensive experimentation and results have been presented.     

Joint wireless and optical resources allocation for availability-guaranteed service in survivable fiber-wireless access network

The fiber-wireless (FIWi) access network not only leverages the technical merits of wireless and optical access networks, but also provides a potential opportunity for the design of survivable access networks. Previous works have studied the survivability of FiWi access network against network component failure by means of backup fiber deployment and wireless rerouting. However, most of these works put less attention on the connection availability and ignore the joint allocation of wireless and optical resources, which plays an important role in improving the global network performance gain. In this paper, we consider a notable failure scenario in FiWi access network but less mentioned in previous works, i.e., single shared-risk link group failure. We first propose a model for FiWi network to estimate the connection availability of service demand. Then, a novel resource allocation approach is proposed to provide the availability-guaranteed service. Under the requirements of bandwidth and connection availability, we deal with the optimal allocation of joint wireless and optical resources with the objective of minimum resource consumption. Numerical results demonstrate that the proposed scheme can reduce the resource consumption significantly compared to the resource allocation without considering connection availability.