Project Completion Probability Research Articles

Stochastic Project Scheduling Optimization for Multi-stage Prefabricated Building Construction with Reliability Application

This study investigates a project scheduling problem of prefabricated building (PB) construction in an uncertain environment. Different from the traditional scheduling models in PB construction, we consider a complex multi-stage cooperation system including the production, transportation and assembly (PTA) phases. In this system, both activity durations and resource amounts are stochastic variables. By applying the reliability theory to the stochastic scheduling model innovatively, we formulate a duration reliability model to maximize the probability of non-delayed project completion, within the resource constraints. As the proposed model is a non-deterministic polynomial hard (NP-hard) problem, a hybrid meta-heuristic differential evolution particle swarm optimization (DEPSO) algorithm is developed, which is utilized the mutation factor of the differential evolution (DE) algorithm in the framework of the particle swarm optimization (PSO). Finally, a real-life example of a PB construction project is used to explore the performance of the proposed DEPSO algorithm. The result shows that the hybrid algorithm DEPSO can better find the global optimal solution in the multi-dimensional optimization problem.

Analysis of 105 IT Project Risks

The article is aimed at increasing the probability of successful IT project completion by identifying the sources of 105 universal risks as well as establishing cause-and-effect relationships between these risks. The article presents the results of an analysis of 105 risks relevant to IT projects; five of them are commercial risks, 45 are compliance risks and 55 are project risks. Risk analysis was carried out using the 5Why, SWIFT and Harrington coefficients. Based on the results of the analysis, the root causes initiating the onset of risks were identified, such as the user, customer, project manager, project team, subcontractor and competitor. Moreover, it was found that the share of the users in the total number of risk sources is 2%, 15% for the customer, 43% for the project manager, 36% for the project team, 2% for the subcontractor and 2% for the competitor. The article also shows models of cause-and-effect relationships of compliance and project risks, presents the results of assessing the risks occurrence probability and their possible impact in cases of materialization, and establishes the most likely and dangerous scenarios in IT projects. The results obtained allowed the development of a criterion to assess the management maturity of a contractor (executor, supplier) planning to develop an computer program as part of an IT project.

'No Man is an Island': An Empirical Study on Team Formation and Performance

Many organizations rely on decentralized arrangements where employees choose their projects and teams. Most of the empirical literature on working collaborations instead focuses on teams that are exogenously formed. I develop a structural entry model with heterogeneous strategic interactions where agents decide whether to join a project. The decision depends on who else may potentially join the project, the project quality, as well as other individual and project characteristics. In turn, this decision affects the probability of project completion. I estimate the model using a novel dataset from an important scientific collaboration. I find that agents' decisions to select into projects highly depend on the pool of teammates and the size of the team whereas projects' quality is of lesser importance. Heterogeneity in agents' characteristics explains this selection, which needs to be accounted for to obtain unbiased estimates of teams' performance. With a counterfactual experiment, I show that moving from a decentralized to a centralized arrangement leads to fewer completed projects.

Analysis of Project Acceleration Implementation Using the CPM and PERT at Lettu Imam Building

The implementation of construction projects generally has a predetermined time limit. To achieve the time limit, planning and controlling are necessary. Planning can determine what work needs to be done and when it is done, what resources are needed, and what risks may arise. Clear activity targets can be identified for each activity. The case study in this research is Lettu Imam Building Construction Project in the OPD Office Complex of Pasuruan Regency. This study uses the Critical Path Method (CPM) to determine the work items passed through the critical path and the Project Evaluation and Review Technique (PERT) to determine the probability of project success. The results of the analysis using the Critical Path Method are 14 work items that were on the critical path A1 - A2 - A3 - B1 - C1 - C2 - C3 - C4 - C5 - C6 - C7 - C8 - C9 - D1. And the result analysis using Project Evaluation and Review Technique has a project completion probability of 89.43% - 99.37%, with the project implementation duration being 162 - 164 days.
 Keywords: Critical Path, Critical Path Method, Planning, Probability, Project Evaluation and Review Technique

Generating a robust baseline schedule for the robust discrete time/resource trade-off problem under work content uncertainty

As a subproblem of the multi-mode resource-constrained project scheduling problem, the discrete time/resource trade-off problem (DTRTP) has occurred widely in practice. This paper tries to generate a robust schedule for the DTRTP with a given due date under uncertainty of the work content. Nine free slack-based measures are adopted as surrogate measures of solution robustness, and a two-stage algorithm based on differential evolution (DE) and the time buffering approach are proposed to deal with the robust model based on the proposed nine different surrogate measures. The computational results show that the three robust models based on a free slack utility function have been proven to be more effective and could generate more robust baseline schedules in most projects with excellent performance, i.e. a low stability cost, a low average project length and a high timely project completion probability.

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

In this paper, we propose a process that combines the Risk Matrix approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Monte Carlo Simulation for assessing risk factors that have an impact on the duration of a construction project’s activities and predict if it is feasible to terminate the project within the prescribed deadlines. Initially, we identified the risks affecting each task of the specific project, and then, we applied the risk matrix approach for determining the probability and impact of every risk to each activity. The resulting ranking is used to assign uncertainty to activities’ durations and estimate the probability of on-time project completion, employing the Monte Carlo Simulation approach. The main contribution of this paper is the development of an innovative framework that coordinates an established qualitative and quantitative risk classification approach, with a popular multicriteria method and a powerful simulation approach, to effectively predict time deviations while executing complex construction projects under uncertainty. The proposed framework was applied to estimate the possibility of a timely execution of an artificial lake real project on the island of Alonissos, Greece. The analysis results illustrate that this approach clearly could help the project risk manager proactively perform risk mitigation measures while allocating budget and programming a project with a significant impact on the quality of life of residents and tourists of a small island.

Terrorism hazard and infrastructure projects: The moderating role of home experience and institutions

This paper analyzes the impact of terrorism hazard on the performance of private participation infrastructure projects. Applying transaction cost theory, we hypothesize that terrorism hazard has a negative relationship with infrastructure project completion, and that host government accountability and investor experience with terrorism hazard have opposing impacts on this relationship. Host government accountability, we argue, produces higher indirect costs of managing terrorism hazard, which reduces investor confidence, and reinforces the negative relationship between terrorism hazard and the probability of satisfactory project completion. Conversely, investor’s experience with terrorism hazard increases investor confidence and hence partially mitigates the negative consequences of terrorism hazard which hamper project completion. Hence, the impact of terrorism is weakened for projects led by firms from higher terrorism hazard countries. We find support for our hypotheses using a sample of 5,083 projects in 135 countries from 2002 to 2017.

Stochastic resource leveling optimization method for trading off float consumption and project completion probability

AbstractExisting resource leveling (RL) approaches fall short of analyzing the trade‐off relation between the total float consumption and project completion probability in a real‐life project RL problem. This article presents a stochastic resource leveling optimization (SOLO) method that minimizes the total float consumption along with maximizing the project completion probability. It initializes the earliest start times of noncritical activities, measures the level of resource fluctuations of each candidate solution, computes the probability of completing a project in a target deadline by executing simulation‐based scheduling, and identifies optimal solution(s) (i.e., optimal start times of noncritical activities) by implementing genetic algorithm, thereby identifying an optimal resource‐leveled baseline. The study is of value to practitioners because SOLO considers both the amount of total float consumption and project completion probability. This study facilitates experimentation with different computation time‐saving options given various constraints (i.e., the residual of project completion probabilities, threshold of release and rehire, ratio of criticality index, and number of critical activities). Test cases verify the validity of the computational method.

ANALISIS PENERAPAN SISTEM PENJADWALAN DENGAN METODE PERT PADA PROYEK KONSTRUKSI (STUDI KASUS: REHABILITASI DAN PENINGKATAN INFRASTRUKSI PASAR TRADISONAL KOTA MALANG)

PERT is a simplified software, to produce the expected project completion probability based on the duration or duration of a particular contract. In developing the PERT method a lot of research was carried out to perfect this method. The purpose of this study is to determine the overall duration of project completion, the magnitude of the project probability that can be completed in less than 170 days and more than 170 days, and the project completion time with the highest probability. Results of Analysis of Implementation of Scheduling System with PERT Method in Rehabilitation and Improvement of Traditional Market Infrastructure Projects in Malang City is the total duration of simulation results obtained 168 days faster than the 172 day plan. The probability of completing the 168 day project is 50%, while the probability of completing the 172 day project is 85.31%. The highest chance of the project being completed is 99.97%, with a duration of 181 days.

Investment Risks by the Reconstruction of the Olympic Sports and Entertainment Complex

The paper examines the reliability of investment risk estimates based on probabilistic realizations of purpose-designed scenarios. The calculations of the probabilities of scenario realization were based on logical and probabilistic methods. The reliability of risk assessment is understood as the probability of successful completion of a project, fulfillment of all contractual obligations: construction in compliance with the architectural and engineering design and quality requirements, within the contractual period and approved budget. Investment risks were estimated based on seven primary scenarios. The realization of the risks of the main group depended on the realization of the various numbers of risk scenarios of each subgroup in the main group. For instance, the first scenario of the main group consisted in the risk of the impact of design errors, including errors in design and estimate documentation, incomplete working documentation. The second one consisted in the risk of the impact of construction errors that determine the quality of construction and installation work, the possibility of industrial accidents, etc. The risks of each subgroup could be obtained by means of expert estimations or, in case of sufficient statistical data, based on the actual distributions. A mathematical model was developed for the purpose of a computerized solution. The mathematical model also allowed identifying such dependability factors as “weight”, “significance” and “contribution” of each risk in the success of an investment project (reliability structure of investment risk estimation). The analysis of calculation data enabled the identification of the probability of successful project completion (reliability), the risks that are the most important, significant and having the largest contribution to the successful implementation of investment projects. Also, the risks were identified that have the least pronounced effect on the successful implementation of an investment project.

Project Completion Probability Analysis Based on Bayesian Network

In the case of not considering the risk, the calculation of the completion probability of the project by Bayesian network will exaggerate the calculation result. Based on this problem, the calculation method of the completion probability of a project affected by risks is proposed. This paper first analyzes the differences between Bayesian network considering risks or not, and establishes a new Bayesian network model based on the advantages of Bayesian network calculating probability and the risk situation encountered in construction. Then, it introduces the calculation method of completion probability considering risk, which mainly includes three types: one is only affected by one of the predecessor activities and risks: the other is affected by both, but the predecessor activities and the current work are not affected by the same risks; the third is the two work are affected by the same risk factors. Calculate the completion probability of the work until the last work based on the above method. Finally, Combined the model with an example to verify its effectiveness. By comparing the completion probability considering risks with that not considering risks, we can see that due to the uncertainty of the environment, the model considering risks has a wider application in the project. It can calculate the completion probability according to the real-time situation and help constructors take measures to ensure its completion in time, which also provides an effective decision basis for project constructors and project builders.

Foreignness in public–private partnerships: The case of project finance investments

The literature on public–private partnerships (PPPs) has begun to identify critical success factors associated with PPP performance. However, despite the international nature of PPPs, the literature has not considered the performance implications of the foreignness of the private sector firm that manages the PPP and its associated infrastructure project. This is a particularly intriguing issue for PPPs, given that the private sector firm is chosen through a bidding process by the host government to lead the project – making the relationship between foreignness and performance potentially endogenous. Our findings suggest that foreignness may have a detrimental effect on project completion time, but not the probability of project completion. Furthermore, the scale and scope of the project moderate the effect of foreignness on project performance. Our findings suggest that governments and policy makers should be mindful that the participation of foreign private sector firms has nuanced implications for local economies and stakeholders impacted by PPPs.

A Construction Schedule Robustness Measure Based on Improved Prospect Theory and the Copula-CRITIC Method

A robustness measure is an effective tool to evaluate the anti-interference capacity of the construction schedule. However, most research focuses on solution robustness or quality robustness, and few consider a composite robustness criterion, neglecting the bounded rationality of subjective weights and inherent importance and nonlinear intercriteria correlations of objective weights. Therefore, a construction schedule robustness measure based on improved prospect theory and the Copula-criteria importance through intercriteria correlation (CRITIC) method is proposed. Firstly, a composite robustness criterion is established, including start time deviation rs and structural deviation rp for measuring solution robustness from project execution and completion probability rc for measuring quality robustness from the project result. Secondly, bounded rationality is considered, using prospect theory to calculate subjective weights, which is improved by the interval distance formula. Thirdly, the Copula-CRITIC method is proposed to determine objective weights incorporating both inherent importance and nonlinear intercriteria correlations. Finally, an information-entropy-based evidence reasoning method is applied to combine subjective and objective weights together while identifying their validity. An underground power station in China is used for a case study, whose robustness is measured using the proposed methods, single robustness criterion, and composite robustness criterion using traditional weighting methods. The comparison results verify the consistency, representativeness, and advantage of the proposed criterion and methods.

Probabilistic assessment of the buildings and structures construction duration

One of the main conditions for achieving the set value of the buildings and structures construction duration is the construction production planning. Due to the fact that the construction process has an uncertain dynamic nature, it is recommended to use probabilistic analytical models to determine such a calculated parameter as the duration. The article proposes a probabilistic model for estimating the duration of construction of buildings and structures on the basis of the normalized Erlang's law of the n-th order. This model allows, by changing the number and duration of work lying on the critical path, to assess the construction project completion probability within the prescribed period.

A Novel Method of Developing Construction Projects Schedule under Rework Scenarios

Construction projects have faced serious schedule delays caused by rework risks. However, it appears that traditional methods are of limited value in developing applicable project schedules. This study presents an analysis on construction projects schedule development under rework scenarios by a novel method named the improved critical chain design structure matrix (CCDSM). Research data are collected from a real estate development project in China. As a result, predictions of project completion duration and probability have been made. A reliable schedule considering information interactions has been developed and visualized. Rework impact areas of activities have been examined to quantitatively record the impact on project duration. To meet different demands, the method generates two more schedules setting different rework buffers. Furthermore, these activities have the potential of causing rework and have been quantified based on the calculation of two criticalities, providing an identification of rework-intensive works that should be payed close importance to, which have not be realized by previous methods. The results proved the feasibility and effectiveness of this method in developing a schedule for construction projects disturbed by rework, helping practitioners adopt measures to avoid rework-caused schedule delays and achieve sustainable development of such projects.

On the reliability of investment risk assessments

The paper examines the reliability of investment risk estimates based on probabilistic realizations of purpose-designed scenarios. The calculations of the probabilities of scenario realization were based on logical and probabilistic methods. The reliability of risk assessment is understood as the probability of successful completion of a project, fulfillment of all contractual obligations: construction in compliance with the architectural and engineering design and quality requirements, within the contractual period and approved budget. Investment risks were estimated based on eight primary scenarios. The realization of the risks of the main group depended on the realization of the various numbers of risk scenarios of each subgroups in the main group. For instance, the first scenario of the main group consisted in the risk of faulty project ROI analysis and the risk of underestimated construction budget. The second one consisted in the risk of underestimated construction budget and risk associated with the selection of the basic flowsheet and primary process parameters, etc. The risks of each subgroup could be obtained by means of expert estimations or, in case of sufficient statistical data, based on the actual distributions. A mathematical model was developed for the purpose of a computerized solution. The mathematical model also allowed identifying such dependability factors as “weight”, “significance” and “contribution” of each risk in the success of an investment project (reliability structure of investment risk estimation). The analysis of calculation data enabled the identification of the probability of successful project completion (reliability), the risks that are the most important, significant and having the largest contribution to the successful implementation of investment projects. Also, the risks were identified that have the least pronounced effect on the successful implementation of an investment project.

A two-stage approach for the critical chain project rescheduling

The fundamental principle of critical chain project management is to use the critical chain instead of a traditional critical path, to insert a project buffer at the end of the project and to insert feeding buffers wherever non-critical chains join the critical chain to protect a timely project completion. Due to the complexity of project, inserting feeding buffers may cause a conflict, such as precedence conflict or resource conflict, which can be solved by rescheduling. However, after rescheduling some new problems may arise: non-critical chain may start earlier than critical chain (non-critical chain overflow), or a gap may occur between activities on the critical chain (critical chain break-down). This paper is aiming to solve these new problems by a two-stage approach combined with feeding buffer for rescheduling. In the first stage, a first-stage rescheduling based on priority rules together with a backward-recursive procedure is proposed for rescheduling to solve resource and precedence conflicts, resulting in a critical chain break-down or a non-critical chain overflow. In the second stage, a second-stage rescheduling based on a heuristic algorithm is proposed to eliminate new problems and generate a better rescheduling scheme. Finally, we do simulations on the 110 Patterson instances set to verify the feasibility, effectiveness and applicability of our two-stage approach for rescheduling. Simulation results show that, it is an effective approach to generate reliable rescheduling schemes in most projects with excellent performances, i.e. the average project length, timely project completion probability and etc.

Governing the Moral Hazard in China’s Sponge City Projects: A Managerial Analysis of the Construction in the Non-Public Land

As a new development mode for solving urban water control problems, a sponge city has been widely concerned and steadily promoted in China. The source engineering in the non-public land is called a low-impact development system. Although it is an important part of a sponge city, the effect of its construction and operation is not ideal at present. The main reason for this lies in the moral hazard behavior of the developer who is the responsible party and the agent. In this research, governance mechanisms for preventing the moral hazard behavior are put forward. Additionally, corresponding models are constructed and designed based on incentive theory and project governance theory. Furthermore, the existence constraint conditions of different governance mechanisms are obtained, as well as the optimal reward and punishment of the government. Meanwhile, this paper calculated the expected returns of the government and the developer. The result shows that project completion probability and supervision cost are two key factors affecting the choice of the governance mechanisms. According to different value of project completion probability and supervision cost, this paper evaluated the selection conditions of different governance mechanisms. Moreover, this research puts forward some governing tactics and suggestions for preventing the developer’s moral hazard behavior, in order to improve the effect of project construction, and promote sponge cities to develop in a more efficient and sustainable manner.

Resource levelling optimization model considering float loss impact

Purpose The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total float loss on risk. Design/methodology/approach An NLIP model is formulated to solve the resource leveling optimization problem incorporating float loss cost (FLC). The proposed model is implemented using “What’s Best solver” for Excel. The FLC is calculated using the float commodity approach. An example is solved using the proposed model in order to illustrate its applicability. Sensitivity analysis is also performed. Findings The results confirmed that resource leveling reduces the available float of non-critical activities; decreases schedule flexibility and reduces the probability of project completion. The probability of timely completion dropped from 50 percent (for the normal schedule with 32 resource fluctuations) to 13.5 percent for leveled resources with zero fluctuations. Using the proposed method, the number of resource fluctuations is 8 but the probability of completing the project on time improved to 20 percent. Practical implications The proposed model allows project managers to exercise new trade-offs between resource leveling and schedule flexibility which will ultimately improve the chances of successful project delivery. Originality/value Resource leveling techniques result in reducing the available total float for the non-critical activities. Existing methods focus on moving noncritical activities within their available float and ignore the impact of the resulting float loss. This reduces the schedule flexibility and increase the risk of project delays. The proposed model incorporates the FLC into the resource leveling optimization problem resulting in more efficient schedules with improved resource utilization while keeping some schedule flexibility.

Reliability interval for a stochastic project network constrained by budget and time

In a project, duration and cost of activities are stochastic in nature due to uncertainties (natural disaster and human factors). Thus, a project is commonly modeled as a stochastic project network (SPN). For a project manager, it is a duty to manage both efficiency and effectiveness of an SPN. To achieve this goal, this paper develops a procedure to derive project reliability interval for an SPN. The project reliability interval is a performance indicator to assess the probability of project completion under budget and time constraints. Such an indicator provides project manager a quantitative measurement and a qualitative implication to decide a reasonable completion time and budget for an SPN. Quantitative measurement shows the efficiency of budget and time consumption to complete a project; while qualitative implication provides the effectiveness after implementing a project. A practical project of disaster recovery system is utilized to demonstrate how the project reliability interval is applicable in the real life. Sensitivity analysis is further implemented to investigate the project reliability interval under various constraints of project time and budget.