scholarly journals Cost Estimate Model for Software Projects using GREYWOLF Algorithm and COCOMO Model

2019 ◽  
Vol 8 (4) ◽  
pp. 7824-7828

Cost estimation analysis for the software system project is the foremost difficult tasks in software organizations. In this paper, a comparison between an estimate and actual effort was done by applying the grey wolf’s algorithm to predict the effort and time of this software system for a given archive. The intermediate semi-detached COCOMO model was used with the grey wolf’s algorithm by taking the KLOC of the dataset as input, additionally to fifteen cost drivers and giving effort and time as output. The recommended model of the cost estimation helps the project manager by offering a fast and truly estimates the hassle and time of software system project which is nearer to the actual cost.

2019 ◽  
Vol 8 (2) ◽  
pp. 3732-3738

In the management of software projects, software cost estimate is very important. The absence of precise and premature estimates is a significant source of the inability of many software initiatives. Nevertheless, it remains a challenge for the software industry to correctly estimate the time and the cost of development. It is used to predict how much effort and time the project needs. The precision of the technology proposal usually depends on the estimated time and the strength standard of the template. In this research analysis the time of development and model fitness are analyzed as a major contribution. The optimized coefficient values for A, B, C & D is used to estimate the time of development and model fitness. This experimental analysis proved that the time of development and model fitness analysis shows the great significance in the estimation and their influence in software cost estimation


This research work is aimed at to provide effective cost estimation methodology emphasize on cost effort and time . This paper summarizes the cost effort estimation of most conventionally used models like organic and semi-detached models using an improved version of genetic algorithm that enhances an empirical methodology to reduce the cost factor and time factor in software projects. Constructive cost model(Cocomo model) is broadly used for the fruitful valuation of cost estimation which is based on KLOC method(thousands of lines of code).This method yields beneficial result in case of lines of code method but lacks in terms of concept and logics. The same is estimated directly and is computed using the function point analysis. In the software development lifecycle, the software cost effort estimation is the most demanding process. The accuracy of the estimate in choosing the estimation model is an essential factor. Such conventional software effort estimation techniques fail to compute the accuracy of effort estimation and it is not up to the mark. So here, we tend to propose the cost reduction in the software projects by using the improved version of the known genetic algorithm.


Author(s):  
Aravindhan K

Cost estimation of software projects is risky task in project management field. It is a process of predicting the cost and effort required to develop a software applications. Several cost estimation models have been proposed over the last thirty to forty years. Many software companies track and analyse the current project by measuring the planed cost and estimate the accuracy. If the estimation is not proper then it leads to the failure of the project. One of the challenging tasks in project management is how to evaluate the different cost estimation and selecting the proper model for the current project. This paper summarizes the different cost estimation model and its techniques. It also provides the proper model selection for the different types of the projects.


2013 ◽  
pp. 675-688
Author(s):  
Ahmed Elragal ◽  
Moutaz Haddara

This chapter is an effort towards illustrating the use of expert panels (EP) as a means of eliciting knowledge from a group of enterprise resource planning (ERP) experts in an exploratory research. The development of a cost estimation model for ERP adoptions is very crucial for research and practice, and that was the main reason behind the willingness of experts to participate in this research. The use of EP was very beneficial as it involved various data collection and visualization techniques, as well as data validation and confirmation. Arguments for using EP over other group techniques are presented in this chapter. Experts modified and enhanced the initial cost drivers list and their sub-factors significantly, as they added, modified, merged and split different costs. Moreover, they ranked the cost drivers according to their weight on total costs. All of this helped the authors to better understand relationships among various cost factors.


2011 ◽  
Vol 264-265 ◽  
pp. 1003-1008 ◽  
Author(s):  
Muataz H.F. Al Hazza ◽  
Erry Yulian Triblas Adesta

Cost structuring of new technology is a critical mission which needs to be developed systematically to get accurate cost estimation. In this research a new approach was proposed and developed for cost structuring a new process. Cost modeling roadmap was proposed to guide the development of genetic cost model by integrating different cost estimating methods and supporting the optimum solution by using statistical techniques in modeling the cost in high speed hard turning, then by building logical relationships between the different effective variables through three levels of cost drivers; main drivers, process and technical drivers and final drivers. Finally a matlab model was developed for simulating the final cost drivers to study the effect of different parameters on the cost drivers.


2011 ◽  
pp. 178-204
Author(s):  
Edit J. Kaminsky ◽  
Holly Danker-McDermot ◽  
Freddie Douglas

This chapter discusses artificial computational intelligence methods as applied to cost prediction. We present the development of a suite of hybrid fuzzy-neural systems for predicting the cost of performing engine tests at NASA’s Stennis Space Center testing facilities. The system is composed of several adaptive network-based fuzzy inference systems (ANFIS), with or without neural subsystems. The output produced by each system in the suite is a rough order of magnitude (ROM) cost estimate for performing the engine test. Basic systems predict cost based solely on raw test data, whereas others use preprocessing of these data, such as principal components and locally linear embedding (LLE), before entering the fuzzy engines. Backpropagation neural networks and radial basis functions networks (RBFNs) are also used to aid in the cost prediction by merging the costs estimated by several ANFIS into a final cost estimate.


Author(s):  
Vоlоdуmуr Matyukha

The importance of cost estimation of mineral resources in modern economic theory is noted in the article. It is noted that all currently existing methodical and methodological approaches to the valuation of minerals by their economic nature are in fact an analysis of the economic feasibility of realization of investment projects for the development of deposits, which actually answers the question: is the investment project for the development of the field economically viable. Based on the analysis of literary sources, it is established that at the present stage of development of the world economy, the interest in the economic evaluation of the efficiency of development of mineral resources is not waning. However, methodological approaches are different and there is still no unity in them. Experts point out that the current methods require improvement due to the low accuracy of calculations, since the size of the cost estimate depends on the amount of rental payments for the use of mineral resources in mining and the starting price of the sale of a special permit for the development of deposits at auction. For the first time in the economic theory economics, a graphoanalytic method for the cost estimation of mineral deposits has been proposed. The features of this methodological approach based on integral calculus, including the integration of continuous functions, as well as the method of discounting cash flows with simultaneous consideration of the life cycle scheme of deposits, namely mining and geological conditions of mining are opened. The step-by-step sequence of realization of the proposed method is resulted. It is stated that this approach will allow to obtain a more exact cost estimate of a deposit or subsoil by taking into account the following factors: the life of the deposit, the market conditions of the mineral resources, capital and current expenses connected with extraction of minerals and costs of the subsoil user in the post-mining a period of time related to the closure of mines and quarries and the reclamation of disturbed lands formed during the extraction of minerals.


2011 ◽  
Vol 17 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Yousef Baalousha ◽  
Tahir Çelik

Estimating is a fundamental part of construction projects. Accurate cost estimate is the single most important element involved in the series of events that leads to a profitable completion of a contract in construction industry. The success or failure of a project depends on the accuracy of cost estimation. A cost estimate becomes more difficult and more complicated under inflationary medium. An unpredictable inflation rate and long progress payment delay during this period makes the budgeting function very difficult, if not impossible. The cost estimation process uses lots of data. The availability of the appropriate data at the appropriate time is one of the main factors affecting the accuracy of the cost estimation. As the complexity of the estimating task increases computerized system becomes increasingly important. The estimator should develop a good system of estimating forms and procedures that exactly meet the requirements of the pro- ject, and that is understood and accessible by all team members. This system should provide the ability to define material, labor hour and equipment hour quantities required for the project. Material, labor, and equipment unit costs are then applied to the bill of quantities. This paper presents An Integrated Web-Based Data Warehouse and Artificial Neural Net- works Model for Unit Price Analysis with Inflation Adjustment system called “DANUP“. Web facilities and database management capabilities of Microsoft Visual Studio 2005 are applied to create a data warehouse which is mainly aimed to integrate data from multiple heterogeneous databases and other information sources. The System also supports integrated cost index for adjusting the effect of inflation during estimating process. An artificial neural network model for forecast- ing the cost indices in Turkey for the project period has been developed. A construction project takes relatively long time to complete, effective communication among the project participants during the project period is important. A web based system is developed to facilitate the collection of construction cost information and communication. The web based sys- tem focuses on demonstrating the potential of data centric web data bases in enhancing the communication process during project execution. End users can access the database through the internet and perform certain transactions according to their authorization. Santrauka Sąmatos sudarymas – esminė statybos projektų dalis. Tiksli sąnaudų sąmata – vienas svarbiausių elementų, susijusių su įvykiais, kurie statybų sektoriuje leidžia pelningai įvykdyti sutartį. Projekto sėkmė arba žlugimas priklauso nuo to, ar tiksliai įvertintos sąnaudos. Infliacinėje aplinkoje sąnaudas įvertinti sunkiau ir sudėtingiau. Dėl neprognozuojamo infliacijos lygio ir ilgalaikių dalinių mokejimų vėlavimo per tokį laikotarpį biudžetą numatyti itin sunku, o gal net neįmanoma. Vertinant sąnaudas reikia gausybės duomenų. Galimybė reikiamu metu gauti reikiamus duomenis – vienas pagrindinių veiksnių, darančių įtaką sąnaudų sąmatos tikslumui. Kadangi sąmatas sudaryti vis sudėtingiau, vis svarbiau yra naudoti kompiuterizuotas sistemas. Sąmatininkas turi suformuoti gerą sąmatų sudarymo formų ir procedūrų sistemą, tiksliai atitinkančią projekto reikalavimus, suprantamą ir prieinamą visiems komandos nariams. Tokioje sistemoje reikia funkcijos, leidžiančios nurodyti projektui reikalingų medžiagų, darbo valandų ir įrangos naudojimo valandų skaičius. Tuomet medžiagų, darbo ir įrangos vienetų kainos įtraukiamos i sąmatą. Šiame darbe pristatoma integruoto internetinio duomenų saugyklos ir dirbtinių neuroninių tinklų modelio, tinkamo analizuoti vieneto kainą, atsižvelgiant į infliacija, sistema, pavadinta ”DANUP“. Naudojant Microsoft Visual Studio 2005 internetines ir duomenų bazių valdymo funkcijas, sukuriama duomenų saugykla, kurios svarbiausias tikslas – integruoti iš daugybės heterogeninių duomenų bazių ir kitų informacijos šaltinių gautus duomenis. Be to, naudojant sistemą galima sudaryti integruotą sąnaudų indeksą, kuris sudarant sąmatą leidžia įvertinti infliacijos poveikį. Buvo sukurtas dirbtinio neuroninio tinklo modelis, leidžiantis Turkijoje prognozuoti sąnaudų indeksus, kurie galios vykstant projektui. Statybos projektas trunka gana ilgai, taigi vykdant projektą svarbu, kad bendravimas tarp jo dalyvių būtų efektyvus. Buvo sukurta internetinė sistema, padedanti rinkti informaciją apie statybų sąnaudas ir bendrauti tarpusavyje. Pagrindinis internetinės sistemos tikslas – parodyti, kaip, remiantis duomenų kiekiu grindžiamomis internetinėmis duomenų bazėmis, vykdant projektą galima pagerinti komunikaciją. Galutiniai vartotojai duomenų bazę gali pasiekti internetu ir, priklausomai nuo prieigos lygio, atlikti tam tikras operacijas.


2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Brajesh Kumar Singh ◽  
Shailesh Tiwari ◽  
K. K. Mishra ◽  
A. K. Misra

Estimation is an important part of software engineering projects, and the ability to produce accurate effort estimates has an impact on key economic processes, including budgeting and bid proposals and deciding the execution boundaries of the project. Work in this paper explores the interrelationship among different dimensions of software projects, namely, project size, effort, and effort influencing factors. The study aims at providing better effort estimate on the parameters of modified COCOMO along with the detailed use of binary genetic algorithm as a novel optimization algorithm. Significance of 15 cost drivers can be shown by their impact on MMRE of efforts on original 63 NASA datasets. Proposed method is producing tuned values of the cost drivers, which are effective enough to improve the productivity of the projects. Prediction at different levels of MRE for each project reflects the percentage of projects with desired accuracy. Furthermore, this model is validated on two different datasets which represents better estimation accuracy as compared to the COCOMO 81 based NASA 63 and NASA 93 datasets.


2003 ◽  
Vol 34 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Magne Emhjellen ◽  
Kjetil Emhjellen ◽  
Petter Osmundsen

Recently, a Norwegian government report on the cost overruns North Sea projects was presented (NOU 1999:11). It concluded that there was a 25% increase in development costs from project sanction (POD, Plan for Operation and Development) to last CCE (Capital Cost Estimate) for the 11 oil field projects investigated. Many reasons like unclear project assumptions in early phase, optimistic interpolation of previous project assumptions, optimistic estimates, and underestimation of uncertainty were given as reasons for overruns. In this paper we highlight the possibility that the cost overruns are not necessarily all due to the reasons given, but also to an error in the estimation and reporting of the capital expenditure cost (CAPEX). Usually the CAPEX is given by a single cost figure, with some indication of its probability distribution. The oil companies report, and are required to do so by government authorities, the estimated 50/50 (median) cost estimate instead of the estimated expected value cost estimate. We demonstrate how the practice of using a 50/50 (median) CAPEX estimate for the 11 projects, when the cost uncertainty distributions are asymmetric, may explain at least part of the “overruns.” Hence, we advocate changing the practice of using 50/50 cost estimates instead of expected value cost estimates for project management and decision purposes.


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