Project Completion Time Research Articles

Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk.

In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.

Risk Analysis on the Construction Project of the Basement Building Under Jalan Pemuda-Yos Sudarso, Surabaya

The basement project that will build under the Pemuda-Yos Sudarso Surabaya road located in the center of Surabaya and the Class A cultural heritage area. The condition is likely to cause many problems during the construction. Such problems could be a risk factor and would affect the completion of the outcome of the work. Therefore the identification of risks to determine how to control risk becomes very important to improve the successful implementation of the project. This study uses questionnaire distributing instruments for respondents and interviews of resource persons deemed competent for risk allocation and risk response. Determination of risk identification variables based on common risk checking where initial risk identification is compiled based on interviews with competent resource persons, previous theoretical and research studies. Data analysis technique is assisted by probability impact matrix and statistical calculation to measure correlation level with Spearman rank followed by an interview with a resource to confirm risk allocation and risk response technique. There identified 28 (twenty-eight) risks; there are 4 (four) risks affecting the cost of completion of the project that is dominant (Unacceptable) and 16 (six)) risks including the category of being or not expected (Undesirable). For the risk of impacting project completion time, there are 5 (five) dominant risks and 17 (seventeen) risks including medium or unexpected category. From the analysis, there are 16 (sixteen) risks that correlate to cost and 23 (twenty-three) risks that correlate to the project completion time. There are 9 (nine) risks allocated by Owner, 4 (four) risks allocated by Design Consultant 8 (eight) risks ownership of Contractor, 1 (one) risk allocation of Supervisory Consultant/CM, 4 (four) risks allocated by Service Provider (Designer, Supervisor / CM, & Contractor), 4 (four) risks as joint risks.

A win-win supply chain solution using project contracts with bargaining games

For product supply chains, contractual relationships that provide win-win outcomes between the supply chain members, have been found to offer optimum results. However, for bargaining situations where time/cost is the source of the uncertainty, i.e. projects, there is limited knowledge available on how contracts can be used to establish win-win relations. This paper investigates whether cost-sharing project contracts can establish a win-win solution in project supply chains where the project manager is risk-neutral and the contractor is risk-averse. The paper examines how the theory can be extended beyond the symmetrical normal distributions to asymmetrical beta and gamma distributions that are more appropriate, and so more often used, for project completion times. Besides using the Nash bargaining approach for analyzing the bargaining process, the paper also analyzes the bargaining problems using the Kalai-Smorodinsky and Utilitarian approaches to bargaining. It was found that the solutions from cost-plus contracts dominate any other form of cost-sharing contract, and so they provide a win-win solution for both members of the supply chain for the cases of Nash and Kalai-Smorodinsky bargaining. However, this is not the case for Utilitarian bargaining. A numerical exercise was conducted to investigate the results and implications of how the models would work in practice. The research shows that from a theoretical perspective, cost-plus contracts are the optimal bargaining solution not only when using a normal distribution, but also when using more appropriate asymmetrical distributions. This optimality is robust for the Nash and Kalai-Smorodinsky bargaining approaches, but not for the Utilitarian approach whose sensitivity to noise makes it an inappropriate choice here.

Resource levelling problem in construction projects under neutrosophic environment

Planning and managing resources is one of the most important topics in project management science. Resource leveling is used for improving work efficiency and minimizing cost throughout the life of the project. Fuzzy resource leveling models assume only truth-membership functions to deal uncertainties conditions surrounded by the projects and their activities duration. In this paper, we consider the objective function of scheduling problem is to minimize the costs of daily resource fluctuations using the precedence relationships during the project completion time. We design a resource leveling model based on neutrosophic set to overcome the ambiguity caused by the real-world problems. In this model, trapezoidal neutrosophic numbers are used to estimate the activities durations. The crisp model for activities time is obtained by applying score and accuracy functions. A numerical example is developed to illustrate the validation of the proposed model in this study.

Practical Analysis and Response for Risks Using Monte Carlo Simulation on Construction Manufacturing

This paper discussed a real project supporting the management of project risk. The model distinguishes between risks which have to be enhanced and risks which can be mitigated or accepted at some cost so that the customer requirements with respect to project completion time can be satisfied at a minimal cost. The model is based on risk management analysis proses and using a Monte Carlo simulation and in order to discover the probability to closure project within the expected date plan. The model is illustrated by means of a real-world case concerning a part of real state residential project construction located in the Republic of Iraq.

Analysing causal relationships between delay factors in construction projects

PurposeAnalyzing factors of delays in construction projects and determining their impact on project performance is necessary to better manage and control projects. Identification of root factors which may lead to project delay and increased cost is vital at the early or planning stage. Better identification of delay factors at the early stage can help the practitioners to reduce their impacts over the long run. Hence, the purpose of this paper is to propose an intelligent method to analyze causal relationships between delay factors in construction projects. The proposed approach is further validated by a real case study of the construction projects in West Azerbaijan province in Iran.Design/methodology/approachDuring the first phase, the fuzzy cognitive map (FCM) is drawn to indicate the causal relationships between the delay factors and the evaluation factors. For this purpose, the causal relationships between 20 delay factors and four evaluation factors are considered. Afterward, the effect of each factor on management goals is evaluated by using a hybrid learning algorithm. Delay factors are further prioritized by applying fuzzy data envelopment analysis (FDEA). In the second phase, an interpretive structural modeling (ISM) is employed to determine the root causes of delay factors.FindingsResults of the first phase show that “supervision technical weaknesses for overcoming technical and executive workshop problems” and “Inaccurate estimation of workload, required equipment and project completion time” are the most significant delay factors. In contrary, “non-use of new engineering contracts” has the lowest impact on the management goals. Meanwhile, the results of the second phase conclude that factors like “Inaccurate estimation of workload, required equipment and project completion time” “weakness of laws and regulations related to job responsibilities” and “lack of foreseen of fines and encouragements in the contracts” are the most significant root factors of delay in construction projects.Originality/valueThis paper integrates three methods including FCM method, FDEA and ISM. In the first phase, FCM is drawn according to the experts’ opinions and concerning management goals and delay factors. Later, these factors are prioritized according to the results of running the algorithm and using the FDEA model. The second phase, the seven-step in the ISM methodology, is done to identify the root factors. To ensure that the root factors of the delay are at a lower level of hierarchical structure, delay factors are partitioned by drawing the ISM model.

PROJECT SCHEDULING AND STAFF ALLOCATION PROBLEM WITH TIME-DEPENDENT LEARNING EFFECT: A MIXED INTEGER NON-LINEAR PROGRAMMING APPROACH

This
 paper proposes a mixed integer non-linear programming (MINLP) for project
 scheduling and staff allocation problem with time-dependent learning effect
 considering task similarities for learning. Resources of a project, especially
 staffs, can learn from previous tasks if those tasks and the current task are
 similar. Considering similarities among tasks for each staff can produce a more
 realistic schedule for a project. The objective function of the proposed
 problem is to minimize project completion time. The learning effect in this
 paper is dependent on the time when the project staff starts to do that task.
 If a project staff does repetitive and/or similar tasks then that staff can get
 experience and do tasks faster than planned durations. Therefore, task sequence
 is essential to assign tasks to project staffs in order to minimize project
 completion time by considering task similarities in view of learning.

PERCEPATAN WAKTU PELAKSANAAN PEKERJAAN KONSTRUKSI DENGAN METODE CPM DAN TCTO

Construction delays are a common and major concern in most construction projects. Construction project delay can indirectly affect of project performance. Delay resolve method is to schedule crashing with various methods. This crashing planning is done by combining the Critical Path Method (CPM) and Time-Cost Trade-Off (TCTO) method for the minimum cost in crash duration calculation. Project A data is used to be a case studi in crash duration calculation and costs increase. Rescheduling with CPM result project completion time 120 days and after crashing project duration becomes 94 days, there was a reduction 26 days project completion time. Crashing programme are do to 18 activities from 30 critical activies rescheduling with CPM result. Total project costs changes is Rp. 19.923.466,- due working time addition (overtime) to reduce project time with Time Cost Trade Off method. Normal condition project costs is Rp. 985,171,182.52 and after duration crash becomes Rp. 1,005,094,648, -.

Optimal project deadlines for mean-variance incentive contract designs

This paper studies contracts that incorporate incentives in the form of bonuses and penalties on top of the contract’s fixed payment and investigates their impact on the project completion time. Its aim is to derive an optimal deadline that maximizes the mean-variance utility function for a risk-averse contractor. By maximizing his payoff utility function, the contractor becomes more motivated to bid for the project, as well as to meet its deadline. It is shown in this paper that under appropriate risk-aversion levels for the contractor, and when the bonus rate in the contract is bigger than that of the penalty, then an optimal deadline that maximizes the risk-averse mean-variance utility function of the contractor exists and is less than the expected mean of the project random duration. This result is in line with many empirical studies and research reports found in the literature which concluded that the bonus in the contract works better than the penalty to incite the contractor to complete the project earlier than planned. In the other case where the bonus rate is less than or equal to the penalty rate, the utility payoff function for the risk-averse contractor is shown to be strictly increasing in terms of the deadline, and therefore, there exists no limit for it. The latter fact cannot therefore work in favor to the contractor. Special cases of famous probability distributions for the project duration were also investigated and their optimal deadlines were derived either in a closed form formula or computed numerically.

Reactive project scheduling: minimizing delays in the completion times of projects

Projects are delayed due to so many reasons. Salient amongst these reasons, in our opinion, is lack of proper planning before the commencement of the project. Many methods exist for the minimization of the completion times of projects. Some methods formulate the problem as resource-constrained project-scheduling problems (RCPSPs) and minimization of project completion time as objective. They find the minimal schedule that minimizes the total completion time of a project while satisfying the precedence and the resource constraints. The basic RCPSP assumes that the renewable resources are periodically renewed and their limited amount can vary from one period to another. The variability of available resource reflects real-life situations. Therefore, with added assumptions to the basic RCPSP, this work proposes a model called hybrid-RCPSP to solve delays in projects. Experimentally, two project examples were used to validate our solution method and it was shown that no matter how small the provided amount for each period, the projects were not unnecessarily delayed.

A dependent project evaluation and review technique: A Bayesian network approach

The Program Evaluation and Review Technique (PERT) dates back to 1959. This method evaluates the uncertainty distribution of a project’s completion time given the uncertain completion times of the activities/tasks comprised within it. Each activity’s uncertainty was defined originally by a unique two parameter beta PERT distribution satisfying what is known to be the PERT mean and PERT variance. In this paper, a three-parameter PERT family of bounded distributions is introduced satisfying that same mean and variance, generalizing the beta PERT distribution. Their additional flexibility allows for the modeling of statistical dependence in a continuous Bayesian network, generalizing in turn the traditional PERT procedure where statistical independence is assumed among beta PERT activity durations. Through currently available Bayesian network software and the construction of that PERT family herein, the coherent monitoring of remaining project completion time uncertainty given partial completion of a project may become more accessible to PERT analysts. An illustrative example demonstrating the benefit of monitoring of remaining project completion time uncertainty as activities complete in that Bayesian fashion shall be presented, including expressions and algorithms for the specification of the three prior parameters for each activity in the project network to adhere to classical the PERT mean and PERT variance and a degree of statistical dependence between them.

Application of critical path method to stochastic processes with historical operation data

The CPM (Critical Path Method) is a network-based approach for project management. This method identifies the longest path, which allows us to find the critical path that must be shortened so that the completion time of the whole project can be shortened. However, considering uncertainty in CPM is not straightforward. In this paper, we consider an optimization problem for stochastic CPM problems, where task durations are expressed as discrete histograms obtained from historical operation data, that maximizes the probability that all tasks are completed within a given completion time by improving the task durations on the critical path. We propose two reformulations of the problem as a mixed-integer linear programming problem: one based on tasks, and the other based on paths. In addition, we propose an iterative method to solve the problem efficiently by reducing the number of binary variables. Finally, we demonstrate efficiency of our proposed methods in some case studies.

An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem

This paper addresses the multi-mode multi-skilled resource-constrained project scheduling problem. Activities of real world projects often require more than one skill to be accomplished. Besides, in many real-world situations, the resources are multi-skilled workforces. In presence of multi-skilled resources, it is required to determine the combination of workforces assigned to each activity. Hence, in this paper, a mixed-integer formulation called the MMSRCPSP is proposed to minimize the completion time of project. Since the MMSRCPSP is strongly NP-hard, a new genetic algorithm is developed to find optimal or near-optimal solutions in a reasonable computation time. The proposed genetic algorithm (PGA) employs two new strategies to explore the solution space in order to find diverse and high-quality individuals. Furthermore, the PGA uses a hybrid multi-attribute decision making (MADM) approach consisting of the Shannon’s entropy method and the VIKOR method to select the candidate individuals for reproduction. The effectiveness of the PGA is evaluated by conducting numerical experiments on several test instances. The outputs of the proposed algorithm is compared to the results obtained by the classical genetic algorithm, harmony search algorithm, and Neurogenetic algorithm. The results show the superiority of the PGA over the other three methods. To test the efficiency of the PGA in finding optimal solutions, the make-span of small size benchmark problems are compared to the optimal solutions obtained by the GAMS software. The outputs show that the proposed genetic algorithm has obtained optimal solutions for 70% of test problems.

Predicting the project time and costs using EVM based on gray numbers

Purpose The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs). Design/methodology/approach The earned value management (EVM) method based on the IGN has been developed. Findings The EVM method based on the IGN has been verified by a numerical example that can be applied to construction projects. Practical implications The EVM method, based on the gray numbers, reduces the budget and time shortage risk. Also, using this method, the managers would not be restricted to provide very exact values in their progress reports in the non-deterministic conditions. Originality/value One notable and significant point in all projects during the execution process is to estimate the project completion time and cost. However, non-deterministic conditions for both planned and actual physical completion percentage of projects have not been considered for predicting the project completion time and cost in the literature. Therefore, the novelty of this paper is the prediction of project completion time and cost under non-deterministic conditions using IGN.

Determination a Reasonable Concession Period for (PPP) Projects

Public Private Partnership (PPP) are agreements where public bodies enter into long term contractual with private entities for construction or management the public sector facilities, or provision services to the community. Internal rate of return (IRR), pay back regime or tariff, and the concession period (CP) are essential items to success (PPP) projects. This research presents a systematic approach for a win-win partnership contract determined on a quantitative basis, by informing the partnership parties how long contract period should be made. Essence of the proposed methodology is that project completion time should allow a competent contractor to complete the project on schedule and operation period should be long enough to enable the concessionaire to achieve a reasonable return, but not too long such that concessionaire’s return is excessive and public sector’s interests are sacrificed. A case study of a PPP project in Mayoralty of Baghdad was conducted to evaluate performance of the developed mathematical models. The determined concession period (CP) has found to be approximately equal to actual concession period (CP) granted to the private sector. Evaluation shows the possibility to adopt the proposed approach to determine the concession period (CP) more effectively. Instead of opportunism policy, the proposed methodology enables local government of Baghdad province to enhance its policies of awarding the partnership projects to increase private sector participation in infrastructure development. Finally, the proposed method can be used by investment practitioners as a decision support tool for contract concession period (CP), and is worth popularizing to design the contracted concession period (CCP) for partnership projects in Iraq, and also can use as a methodology to assess the critical aspects which related to partnership projects in general.

Using PERT to Optimise the Completion Time of Air-Conditioning and Mechanical Ventilation (ACMV) Project

An air-conditioning and mechanical ventilation (ACMV) construction project involved many interrelated construction activities with varying durations and multiple dependencies. This paper focuses on the development of a best possible project planning and scheduling technique that can help the project manager to manage and complete the ACMV project in optimal time. The program evaluation and review technique (PERT) is used in this research. The PERT technique helps to determine the probabilities of various stages of the project by specified deadlines and identify the activities on the critical path that have high potential for causing delays in the project completion time. The completion times of 72, 76, 79, and 80 weeks were taken for the PERT analysis. Deadline of 72 weeks is the contractual period of the ACMV project as specified in the contract. Completion time of 76 weeks is the critical path of the project as analyzed by the PERT technique. The deadline of 79 weeks is the proposed completion time for the ACMV project whereas 80 weeks are the actual completion date of the project. The PERT analysis revealed that the project completion time of 72 weeks, which is as stated in the contractual completion time, yielded the probability of completion of 2.67% only. This analysis shows that the contractual period is impossible to be achieved and it is an unrealistic time setting. Further negotiation is required including changing or extending of the contractual completion time. The other completion times are able to be achieved but the company may need to face the high penalty costs due to the delays in completion time.

Analisa Jaringan Kerja dengan Metode CPM pada Proyek Pembangunan Gedung Balai Diklat BPK RI Perwakilan Provinsi Sumatera Utara di Medan

<p><em>Research was conducted at the training center bulding projec RI BPK Representative in Medan, North Sumatera, where the purpose of this research is to create a complex framework of activities based on project completion time and human resources available for job creation building structures manager. The framewwork presented in the form of work flow diagram (Network Diagram). From the data obtainned by the completion of the project structure has been estimated tim required to finish the job thus structure with the critical path method (Critical Path Method – CPM). After the calculation of forward and backward calculation is obtained : fastest tim starting and completion activities, no later than beginning and completion of, the lenght of the interval delay /postponement of activities. With the CPM method, completion building structure mnagement training center of RI BPK representative of North Sumatera Province is known than the sum of time critical activities. These critical activities each time interval did not have to delay the implementation of activities. The activities that are on the critical path is the activity with the notation : A-C-E-F-I-L-MQ-U-V-W-X-Y-Z-AA-AC-AD gained 4+9+6+6+1+3+6+1+1+6+1+6+6+1+6+1 = 64 days.</em></p>

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

This paper proposes a credibility based chance constrained programming approach for project scheduling problems with fuzzy activity durations where the objective is to minimize the fuzzy project completion time. This paper expresses the fuzzy events such as a project activity’s duration or project completion time with fuzzy chance constraints and the chance of a fuzzy event is illustrated with fuzzy credibility distribution. Due to uncertainty in durations of a project, fuzzy sets and fuzzy numbers can be used in order to illustrate the uncertainty and find a solution space for the problem. Therefore, fuzzy credibility based chance constraint technique is investigated for project scheduling problems with fuzzy activity durations considering the uncertainty or chance of a fuzzy event within a closed interval. In this paper, a fuzzy mathematical model and its crisp equivalent by using credibility measure and chance-constrained programming are given for project scheduling problems with fuzzy activity durations.

Key uncertainty events impacting on the completion time of highway construction projects

This paper examines the uncertainty events encountered in the process of constructing highways, and evaluates their impact on construction time, on highway projects in South Africa. The rationale for this examination stems from the view held by scholars that the construction of highways is a complex process, taking place in changing environments and often beset by uncertainties; and that there is a lack of appropriate evaluation of these uncertainty events occurring during the construction process. The research made use of a review of extant literature in the area of uncertainty management, and modeling in infrastructure projects, to guide the direction of the study. The inquiry process consisted of brainstorming by highway experts and interviewing them to identify the uncertainty factors that impact construction time. An uncertainty matrix for South African highway projects was developed, using a quantitative model and descriptive statistics. It emerged from the study that the uncertainty events affecting the construction time of highway projects are distributed across economic, environmental, financial, legal, political, social and technical factors. Also, it was found that each factor might account for several uncertainty events which impact on construction time differently, through a combination of the uncertainty events of the individual construction activities. Based on the obtained data, an Adaptive Neuro Fuzzy Inference System (ANFIS) has been developed, as a simple, reliable and accurate advanced machine learning technique to assess the impact of uncertainty events on the completion time of highway construction projects. To validate the ANFIS model, the Stepwise Regression (SR) models have been designed and their results are compared with the results of the ANFIS. Based on the predicted impact size of uncertainty events on the time of highway projects, it can be concluded that construction time on South African highway projects is significantly related to the social and technical uncertainties factors.

TIME OPTIMIZATION USING CPM, PERT AND PDM METHODS IN THE SOCIAL AND DEPARTMENT OF KELAUTAN BUILDING DEVELOPMENT PROJECT GRESIK DISTRICT

Planning a project there are many important things that affect the success and smoothness, one of which planning time implementation of the right and efficient work. The way to overcome the problem is by using several methods such as CPM (Critical Path Method), PERT (Project Evaluation and Review Teqnique), PDM (Precedence Diagram Method). From the calculation result show that the duration of project completion using CPM method is 57 weeks, project completion duration using PERT method is 78 + 7.5 weeks with the probability of achieving project completion time target is 99.87% and project completion duration using PDM method is 30 weeks. So the method that best suits the Social Service Development Project and the Office of Marine Gresik Regency is the PDM method because the PDM method is capable of producing shorter project completion periods than the CPM and PERT methods of 30 weeks.