scholarly journals Prediction of Cost Overrun Risk in Construction Projects

2020 ◽  
Vol 12 (22) ◽  
pp. 9341
Author(s):  
Edyta Plebankiewicz ◽  
Damian Wieczorek
Keyword(s):  
Prediction Model ◽  
Construction Projects ◽  
Fuzzy Inference ◽  
Unit Price ◽  
Design Stage ◽  
Rule Base ◽  
Cost Overrun ◽  
Single Output ◽  
General Contractors ◽  
Input Variables

The paper proposes a cost overrun risks prediction model, the structure of which is based on the fuzzy inference model of Mamdani. The model consists of numerous inputs and one output (MISO, multi-input-single-output), based on processes running consecutively in three blocks (the fuzzy block, the interference block, and the block of sharpening the representative output value). The input variables of the model include the share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC). The developed rule base makes it possible to determine the risk of cost overruns in the following categories: “very low”, “quite low”, “average”, “quite high”, and “very high”. Twenty-seven rules were assumed in the interference block. The operation of the model was illustrated by the example of selected elements of a road object and was validated by checking the correctness of the assumptions made at the design stage of the inference block rule base. It has been proven that with the increase of the share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC), the value of the risk exceeding the costs of a given element of the construction project (R) increases naturally and smoothly. It was emphasized in the conclusions that the cost overrun risks prediction model is intended for general contractors who subcontract many stages of works to their subcontractors in accordance with the agreed division into work elements.

scholarly journals Risks of Design Stage in Iraqi Construction Project

2018 ◽  
Vol 24 (3) ◽  
pp. 114
Author(s):  
Alaa Kharbat Shadhar ◽  
Buroog Basheer Mahmood
Keyword(s):  
Construction Projects ◽  
Construction Project ◽  
Fast Response ◽  
Unit Price ◽  
Design Stage ◽  
Project Completion ◽  
Lump Sum ◽  
Full Study ◽  
Effect Level ◽  
Design Documents

The management of construction projects needs to complete the basics of system management and work. Starting from the idea and how to turn it into a full study and ended at the construction project completion arriving at the purpose prepared for it, so the projects need to control on its operation and integration system in order to succeed. It is no secret for who concerned in construction projects field that the design stage is a very important stage in construction project because it determines the final features of the project through the requirements provided by the employer for the consultant to formulate it during this phase in the form of plans, drawings, and specifications, then translated on the ground as the shape of completed project meets those requirements. Therefore it has been necessary to focus in this paper on the design stage also demonstrated and analysis the most important risk facing this stage and their impact on a construction project by introducing a questionnaire to identify the most important risks factors at this stage affecting on the project. The paper had been shown that the effect of the design stage on Lump sum type of project contract was higher than the unit price, while the most important factor effect on a project its fast response of design team to prepare the design documents in order to facilitate the workflow and sequence of execution with effect level 3.714.    

Key indicators of rice production and consumption, correlation between them and supply-demand prediction

2015 ◽  
Vol 64 (8) ◽  
pp. 1113-1137
Author(s):  
Sanjay Sharma ◽  
Sanjaysingh Vijaysingh Patil
Keyword(s):  
Growth Rate ◽  
Correlation Analysis ◽  
Fuzzy Inference ◽  
Rule Base ◽  
Inference System ◽  
Content Type ◽  
Production And Consumption ◽  
Per Capita ◽  
Input Variables ◽  
Insignificant Correlation

Purpose – The purpose of this paper is to establish correlations among the input variables of production within themselves and input variables of consumption within themselves and to forecast the production and consumption of the rice. Design/methodology/approach – The production and consumption of rice crop is governed by diverse variables. In the present study five key input variables for production of rice based on literature review and the authenticated data available from agricultural sources have been selected. These variables are area sown, agricultural workers (AW), area irrigated, growth rate and yield per hectare. On similar basis four key input variables responsible for consumption of rice are considered, namely, price of rice, population, poverty ratio and per capita net national product (NNP). Findings – Correlation analysis showed that priority wise production of rice depends upon yield per hectare, percentage irrigation, AW and area sown. The growth rate is found to be having insignificant correlation with other variables of production and hence was omitted from subsequent study. Correlation analysis also showed that priority wise consumption depends upon whole sale price per ton, population and the per capita NNP. The poverty ratio is found to be having insignificant correlation with other variables of consumption and hence was omitted from subsequent study. The outcomes of the correlation analysis are utilized for designing rule base for fuzzy inference system (FIS) to forecast the production and consumption of the rice. Subsequently Bayesian technique is used to forecast production and consumption and its results are compared with the results of fuzzy inference analysis. Originality/value – There are many techniques used for forecasting purpose but FIS and Bayesian technique outperform others. In the present study, the authors therefore focussed on these two techniques. Bayesian technique takes into account the expert opinion at the current conditions whereas FIS uses previously designed rule base. Besides discussing the appropriateness of these two techniques for forecasting production and consumption of rice, their forecasting outcomes will help in logistical and operational planning of the resources at national level, farmers’ level and traders’ level.

scholarly journals Application of fuzzy modeling in the evaluation of crisis state of enterprises

2019 ◽  
pp. 66-71
Author(s):  
M. N. Belousova ◽  
A. A. Dashkov
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Model ◽  
Rule Base ◽  
Software Environment ◽  
Inference Procedure ◽  
Relative Level ◽  
Inference System ◽  
Innovation Potential ◽  
Input Variables ◽  
Fuzzy Assessment

The features of the proposed fuzzy model for assessing the crisis state of enterprises have been disclosed. The MATLAB software environment has been selected as the environment for building a fuzzy output system. In the model of a fuzzy assessment of the crisis state of enterprises, the following input linguistic variables have been highlighted: the relative level of financial status, the probability of bankruptcy, the level of information security, the level of innovation potential. The terms of the input variables and the result variable have been described. The rule base for fuzzy inference system has been formulated. The results of modeling the assessment of the crisis state of enterprises have been represented by a fuzzy inference procedure.

scholarly journals Analiza wrażliwości modelu sterowania relacjami partnerskimi na zmiany funkcji przynależności zmiennych

2017 ◽  
Vol 26 (2) ◽  
pp. 219-225 ◽  
Author(s):  
Elżbieta Radziszewska-Zielina ◽  
Bartłomiej Szewczyk
Keyword(s):  
Construction Projects ◽  
Fuzzy Inference ◽  
Assessment Criteria ◽  
Quality And Safety ◽  
Membership Functions ◽  
Time Cost ◽  
Project Assessment ◽  
Input Variables ◽  
The Impact

The article analyzes the previously developed model controlling partnering relations in construction projects. This model is based on Mamdani fuzzy inference. Its input variables include: current assessments of particular partnering relation parameters, the weights of these parameters’ impact on time, cost, quality and safety of implementation of construction projects, as well as importance of these project assessment criteria for its manager. On the basis of the recommendation is determined to control, for each partnering relation parameter. In the article the influence of the type of membership functions for model variables on the obtained results has been investigated. The analysis has shown that the impact is insignificant.

scholarly journals OPTIMIZED MANAGEMENT STRATEGY FOR CONSTRUCTION PROJECTS CONSIDERING THE TRADE-OFF OF ESTIMATE SCHEDULE AND COST AT COMPLETION

2019 ◽  
Vol 6 (2) ◽  
pp. 26-37
Author(s):  
Liem Stefani Meilia Gunawan
Keyword(s):  
Prediction Model ◽  
Construction Projects ◽  
Indifference Curve ◽  
Cost Overrun ◽  
Cost Performance ◽  
Trade Off ◽  
Project Duration ◽  
Pareto Curve ◽  
Uncertain Factor ◽  
Direct Equation

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. In this research, SOS-NN-LSTM is required to establish the estimate schedule to completion (ESTC) and estimate cost to completion (ECTC) prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between estimate schedule at completion (ESAC) dan estimate cost at completion (ECAC) which give the decision-maker preference.

scholarly journals Adaptation of a Cost Overrun Risk Prediction Model to the Type of Construction Facility

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1739 ◽  
Author(s):  
Edyta Plebankiewicz ◽  
Damian Wieczorek
Keyword(s):  
Prediction Model ◽  
Risk Prediction ◽  
Residential Buildings ◽  
Center Of Gravity ◽  
Risk Prediction Model ◽  
Cost Overrun ◽  
Gravity Method ◽  
Input Variables ◽  
The Cost ◽  
The Impact

To assess the risk of project cost overrun, it is necessary to consider large amounts of symmetric and asymmetric data. This paper proposes a cost overrun risk prediction model, the structure of which is based on the fuzzy inference model of Mamdani. The model consists of numerous inputs and one output (multi-input-single-output (MISO)), based on processes running consecutively in three blocks (the fuzzy block, the interference block, and the block of sharpening the representative output value). The input variables of the model include the share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC). For the input variable SE, it is proposed to adjust the fuzzy set shapes to the type of building object. Single-family residential buildings, multi-family residential buildings, office buildings, highways, expressways, and sports fields were analyzed. The initial variable is the value of the risk of exceeding the costs of a given element of a construction investment project (R). In all, 27 rules were assumed in the interference block. Considering the possibility of applying sharpening methods in the cost overrun risk prediction model, the following defuzzification methods were investigated: the first of maxima, middle of maxima, and last of maxima method, the center of gravity method, and the bisector area method. Considering the advantages and disadvantages, the authors assumed that the correct and basic defuzzification method in the cost overrun risk prediction model was the center of gravity method. In order to check the correctness of the assumption made at the stage of designing the rule database, result diagrams were generated for the relationships between the variable (R) and the input variables of individual types of buildings. The results obtained confirm the correctness of the assumed assumptions and allow to consider the input variable (SE), adjusted individually to the model for each type of construction object, as crucial in the context of the impact on the output value of the output variable (R).

Contractor default prediction model for surety bonding1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

2012 ◽  
Vol 39 (9) ◽  
pp. 1027-1042 ◽  
Author(s):  
Adel Awad ◽  
Aminah Robinson Fayek
Keyword(s):  
Prediction Model ◽  
Fuzzy Inference ◽  
Evaluation Criteria ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Self Assessment ◽  
Inference System ◽  
Management Evaluation ◽  
Novel Approach ◽  
Default Prediction

Contractor default is one of the major risks that threaten a project’s success in the construction industry. Previous studies have focused mainly on evaluation of the contractor’s financial aspects to predict contractor default. There remains a need for a comprehensive model that has the ability to incorporate the evaluation of all the project aspects, project team, contractual risks, and project management evaluation criteria to predict the possibility of a contractor’s default on a specific construction project. This paper presents a contractor default prediction model (CDPM) from the surety bonding perspective that incorporates these criteria and uses a fuzzy inference system for reasoning. The CDPM provides a more objective, structured, and comprehensive approach for contractor default prediction for surety practitioners, project owners, and for self-assessment by contractors to reduce the risk of contractor default. The multi-attribute utility function was used to develop a group consensus system (GCS) to aggregate the participating experts’ opinions to build the CDPM. The accuracy of the GCS was found to be 91.1%. A novel approach for fuzzy rule base development is applied to develop the rule base for the CDPM. The CDPM was validated using 30 contractor default prediction cases, and the accuracy was found to be 86.5%.

scholarly journals Model of Predicting Cost Overrun in Construction Projects

2018 ◽  
Vol 10 (12) ◽  
pp. 4387 ◽  
Author(s):  
Edyta Plebankiewicz
Keyword(s):  
Prediction Model ◽  
Cash Flow ◽  
Construction Projects ◽  
Cost Overrun ◽  
Fuzzy Relations ◽  
Inference Method ◽  
Total Cost ◽  
The Cost ◽  
Selection Of ◽  
Construction Works

During the construction phase, significant differences between the planned and actual costs of construction projects frequently occur. The paper describes the concept of a model of prediction of the increase in the costs of construction works in relation to those planned. The assumption of the model is to determine the probability of the cost increase for the elements of the object for which it is the largest. A fuzzy Mamdani inference method was proposed for the selection of the elements to be evaluated. In the cost prediction model, fuzzy relations and the compound max-min relations were used. The result of the model are the probabilities of cost overrun for works most exposed to changes in costs. The model can be helpful mainly for the contractor who wants to know not only the probability of the total cost overrun but also the possibility and amount of increase in the costs of individual packages of works or detailed construction works necessary to complete a construction project. Such an approach may help to properly plan expenses related to the implementation and schedule of works along with the cash flow for the project.

Investigation of Cost-Influencing Factors Potentially ‎Controllable by Main Contractors in Construction Projects in ‎Iraq

2020 ◽  
Vol 38 (7A) ◽  
pp. 1069-1076
Author(s):  
Layth T. Ali ◽  
Raid S. Abid Ali ◽  
Zeyad S. M. Khaled
Keyword(s):  
Construction Projects ◽  
Project Managers ◽  
Cost Overrun ◽  
Public And Private ◽  
Importance Index ◽  
Labor Recruitment ◽  
Supply Planning ◽  
Major Factors ◽  
And Control ◽  
The Impact

Cost overrun in construction projects is a common phenomenon in Iraq. This might occur due to diversity of factors. This study aims to identify the factors influencing construction projects cost that are potentially controllable by main contractors. A field study through a questionnaire survey was directed to a sample of related Iraqi professional engineers from general contracting companies at both public and private sectors. Their opinions on the impact and frequency of each factor were investigated. The questionnaire offered (59) factors classified in (8) categories namely; legislations, financial and economic, design, contractual, site management, material, labor and equipment. The factors were ranked according to the highest Relative Importance Index (RII). The study revealed (10) major factors that are potentially controllable by main contractors namely; labor productivity, sub-contractors and suppliers performance, equipment productivity, site organization and distribution of equipment, experience and training of project managers, scheduling and control techniques, planning for materials supply, planning for equipment supply, materials delivery and planning for skilled labor recruitment. Recommendations to aid contractors and owners in early identification of these factors are also included in this study.

Inhibiting Factors of Cost Performance in UAE Construction Projects

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Ahmed Salem Ahmed Marey Alhammadi ◽  
◽  
Aftab Hameed Memon ◽  
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Past Research ◽  
Cost Overrun ◽  
Index Method ◽  
Cost Performance ◽  
Factors Affecting ◽  
Inhibiting Factors ◽  
Critical Problems ◽  
Structured Questionnaire

UAE construction industry frequently faces poor cost performance which commonly known as cost overrun problem. This problem is resulted from several factors and it is important to identify these cost overrun factors in order to avoid and minimize it. Hence, this paper focused on determined the relevancy of factors affecting cost performance in construction projects of UAE. Through a review of past research works conducted globally, 27 factors of cost overrun were listed and used for developing a structured questionnaire. A survey was conducted with 33 practitioners from client, consultant and contractors organizations involved in handling construction projects in UAE. The respondents were requested to state their perception regarding the relevancy of each of the factors that was perceived in context with cost overrun issue using 5-points Likert scale. The responses were analysed using average index method and the results found that all the 27 factors are relevant with construction industry of UAE in causing cost overrun. These factors can be used for further investigation to uncover critical problems of cost overrun.

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