Projects Never Fail: A Critical Review on Estimation of Project Scheduling and Project Costing

Uncertainty remains common in all projects. It is need to realize this uncertainty and have to minimize the effect of this uncertainty to achieve better project outcomes. To realize the project on truthful base it is required to develop project schedule and estimate project costing on reality bases. A lot of project scheduling and costing techniques and tools are used to measure the accuracy. The new systematic techniques increase project outcomes and also reduce the uncertainty from the projects.  This study will leads to examine thoroughly project scheduling and project costing. Then this study will guide project managers how to develop a project schedule and what factors are effecting on the project scheduling and a sample project schedule will also provide for project managers and students of project management. After that the major sources of project costing and the method to calculate the project cost will also provide. And the sample project costing sheet is also develop in this study. Both project scheduling and project costing will develop the professionalism among project managers and students of project managers which they can never think before this study and also enhance project outcomes. Keywords: Project Scheduling, Project Costing, Uncertainty Handling and Project Succes

A Grey-Based Fuzzy ELECTRE Model for Project Selection

Project selection is considered as an important problem in project management. It is multi-criteria in nature and is based on various quantitative and qualitative factors. The main purpose of this paper is to present a new rank-based method for project selection in outranking relation. According to this approach, decision alternatives were clustered in the concordance matrix and the discordance matrix through the ELECTRE model based on intuitionistic trapezoidal fuzzy numbers. Then, the two matrices were integrated and ranked using grey relational coefficients and the Minkowski space distance. The results of the model were compared with grey relational projection method with intuitionistic trapezoidal fuzzy number. To illustrate the proposed methodology, a case study was conducted to select National Iranian Oil Company projects

Combined model of optimal electricity production: Evidence from Ukraine

У статті запропоновано методологію формування комбінованої моделі рівноважних значень ціноутворення та обсягів виробництва електроенергії з урахуванням зелених та традиційних джерел виробництва електроенергії на прикладі України. Відповідно до прогнозної ціни та обсягів виробництва електроенергії у 2021 році розглянуто модель перерозподілу джерел електроенергії з урахуванням мінімізації бюджетних ресурсів та ризику виробництва електроенергії з відповідним обмеженням виробництва різних видів електроенергії та їх вплив на мінімізацію ціни для кінцевого споживача. Проведені дослідження показали, що важливими чинниками формування ціни на електроенергію є показники собівартості та обсягів виробництва, розподілу та транспортування електроенергії споживачам, від яких значною мірою залежить формування та подальший розвиток енергетичного ринку України. Також велике значення має перерозподіл обсягів традиційної та нетрадиційної електроенергії в спільній «каструлі» при мінімізації ризиків та бюджетних обмежень. Збалансування системи генерації електроенергії з різних джерел допоможе не тільки оптимізувати довгострокові ціни на електроенергію та мінімізувати тарифи для кінцевого споживача, але й дозволить планувати прибуток у вигляді довгострокової ринкової окупності інвестицій. Аналіз результатів показав, що оптимальний розподіл виробництва енергії дає можливість отримати енергоресурси в необхідному обсязі з меншими витратами на придбання та з мінімальним ризиком.В статье предложена методология формирования комбинированной модели равновесных значений ценообразования и объемов производства электроэнергии с учетом зеленых и традиционных источников производства электроэнергии на примере Украины. В соответствии с прогнозной ценой и объемами производства электроэнергии в 2021 году рассмотрена модель перераспределения источников электроэнергии с учетом минимизации бюджетных ресурсов и риска производства электроэнергии с соответствующим ограничением производства различных видов электроэнергии и их влияние на минимизацию цены для конечного потребителя. Проведенные исследования показали, что важными факторами формирования цены электроэнергии являются показатели себестоимости и объемов производства, распределения и транспортировки электроэнергии потребителям, от которых в значительной степени зависит формирование и дальнейшее развитие энергетического рынка Украины. Также большое значение имеет перераспределение объемов традиционной и нетрадиционной электроэнергии в «кастрюле» при минимизации рисков и бюджетных ограничений. Сбалансирование системы генерации электроэнергии из разных источников поможет не только оптимизировать долгосрочные цены на электроэнергию и минимизировать тарифы для конечного потребителя, но позволит планировать прибыль в виде долгосрочной рыночной окупаемости инвестиций. Анализ результатов показал, что оптимальное распределение производства энергии позволяет получить энергоресурсы в необходимом объеме с меньшими затратами на приобретение и с минимальным риском.The article proposes a methodology for the formation of a combined model of the equilibrium values of pricing and the volume of electricity production, taking into account green and traditional sources of electricity production on the example of Ukraine. In accordance with the projected price and volume of electricity production in 2021, a model for redistributing electricity sources were considered, taking into account the minimization of budgetary resources and the risk of electricity production with appropriate restrictions in the production of various types of electricity and their impact on minimizing the price for the end user. The studies have shown that important factors in the formation of electricity prices are indicators of the cost and volume of production, distribution and transportation of electricity to consumers, which largely depends on the formation and further development of the energy market in Ukraine. Also, the redistribution of the volumes of traditional and non-traditional electricity in the common “pot” is of great importance while minimizing risks and budgetary constraints. Balancing the system for generating electricity from various sources will help not only optimize long-term electricity prices and minimize tariffs for the end user, but also allow planning profit in the form of long-term market return on investment. The analysis of the results showed that the optimal distribution of energy production makes it possible to obtain energy resources in the required volume with lower purchase costs and with minimal risk

A FUZZY BI-LEVEL PROJECT PORTFOLIO PLANNING CONSIDERING THE DECENTRALIZED STRUCTURE OF PHARMACY HOLDINGS

Research and development (R&D) in the pharmaceutical industry requires proper and optimal planning and management because of its critical role in public health. Taking into account a decentralized decision-making structure in R&D management in pharmaceutical holding companies, this study introduces a new fuzzy bi-level multi-follower mathematical optimization model to address budget allocation and project portfolio planning. Specifically, the holding company's head office, as the leader, and the subsidiaries, as followers, make strategic and operational decisions concerning important issues such as budget allocation and portfolio selection and scheduling. Since the lower level represents multiple mixed-integer programming problems with uncooperative reference relationships between followers, solving the resulting bi-level model is challenging. Therefore, our model is based on an effective hybrid solution methodology, which converts the bi-level model, including multiple followers, into a single-level model. In order to validate the proposed model, we conducted a case study and analyzed the strategies of each actor within the conglomerate. Based on the results of experiments, it is evident that a strategy that focuses on one level of operations profoundly affects decisions at the other level

Risk assessment and optimal scheduling of serial projects

The valuation and planning of complex projects are becoming increasingly challenging with rising market uncertainty and the deregulation of many industries, which have also raised the need for efficient risk management. We take the perspective of a private firm interested in sequential capacity expansion of a project and develop a framework for measuring the downside risk of the serial project and optimising the sequence of the stages. Under general distributional assumptions for the duration of each stage, we present an accurate representation of the project’s net present value (NPV) distribution based on a Pearson curve fit, leading to closed-form expressions for the associated risk measures. We then assess the impact of duration variability on the value at risk and demonstrate its role in stochastic project scheduling. We also account for the trade-off between maximising the expected NPV and minimising the risk exposure, and obtain the optimal schedule for risk-averse decision-makers. It becomes obvious that both the duration variability of each stage and the decision-makers’ risk preferences can significantly affect the optimal sequence of the stages and that high duration variability is not always undesirable, even for risk-averse decision-makers

Mathematical Model and Framework for Multi-Phase Project Optimization

This research aims to assist investors of “real” tangible assets such as construction projects in making an optimal portfolio of phased and regular projects which will yield the best financial outcome calculated in terms of discounted cash flow of future anticipated revenues and costs. We use optimization techniques to find the optimal timing and phasing of a single project that has the potential of being decomposed into smaller sequential phases. Existence of uncertainties is inevitable especially in cases in which we are planning for long durations. In the presence of these uncertainties, full upfront commitment to large projects may jeopardize the rationality of investments and cause substantial economic risks. Breaking a big project into smaller stages (phases) and implementing a staged development is a potential mechanism to hedge the risk. Under this approach, by adding managerial flexibilities, we may choose to abandon a project at any time once the uncertain outcomes are not favorable. In addition to the benefits resulting from hedging unfavorable risks, phasing a project can transform a financially infeasible project into a feasible one due to less load on capital budgets during each time. Once some phases of a project are delayed and planned to be implemented sequentially, it is important to prepare the infrastructure required for their future development. Initially, we present a Mixed Integer Programming (MIP) model for the deterministic case with no uncertainties that considers interrelationships between phases of projects such as scheduling and costs (economy of scales) in addition to the initial infrastructural investment required for implementation of future phases. Pairing possible phases of a project and doing them in parallel is beneficial due to positive synergies between phases but on the downside requires larger capital investments. Unavailability of enough budgets to fully develop a profitable project will cause the investment to be carried out in different phases e.g. during times when the required capital for developing the next phase (or group of phases) is available. After, presenting the model for the deterministic case, we present a scenario-based multi-stage MIP model for the stochastic case. The source of uncertainty considered is future demand that is modeled using a trinomial lattice. We then present two methods for solving the stochastic problem and finding the value of the here and now decision variable (the size of the infrastructure/foundation). Finding the value of the here and now decision variable for all scenarios using a novel technique that does not require solving all the scenarios is the first method. The second method combines simulation and optimization to find good solutions for the here and now decision variable. Lastly, we present a MIP for the deterministic multi-project case. In this setting, projects could have multiple phases. The MIP will help the managers in making the project selection and scheduling decision simultaneously. It will also assist the managers in making appropriate decisions for the size of the infrastructure and the implementation schedule of the phases of each project. To solve this complex model, we present a pre-processing step that helps reduce the size of the problem and a heuristic that finds good solutions very fast

Finansinių išteklių paskirstymas projektų portfelyje atsižvelgiant į darnumo aspektus

Disertacijoje nagrinėjamas finansinių išteklių paskirstymas projektų portfelyje. Literatūros analizė atskleidė, kad šiuo metu darnumas yra vienas svarbiausių klausimų, į kurį reikia atsižvelgti priimant sprendimus įvairiuose į projektus orientuotos įmonės lygmenyse. Vis labiau įsitikinama, kad reikia sukurti priemones siekiant integruoti darnumo kriterijus į projektų portfelio valdymą, taip pat atsiranda vis didesnis žinių, kaip įdiegti darnumą projektų portfelio valdymo procese, poreikis. Šiame darbe siekiama susieti šias dvi mokslines tyrimo sritis sprendžiant finansinių išteklių paskirstymo projektų portfelyje klausimą. Pagrindinis disertacijos tikslas – pasitelkiant daugiakriterinius sprendi-mų priėmimo metodus, sukurti ir praktiškai pritaikyti finansinių išteklių paskirstymo projektų portfelyje modelį, leidžiantį formuoti sprendimus, atsižvelgiant ne tik į projekto grąžą ir riziką, bet ir į darnumo aspektus. Darbe sprendžiami tokie pagrindiniai uždaviniai: siekiama sudaryti sudėtinį pro-jekto darnumo indeksą, sukurti finansinių išteklių paskirstymo projektų portfelyje modelį, integruojant darnumo indeksą į Markowitz vidurkio-dispersijos modelį, empiriškai patikrinti modelio pritaikomumą bei įvertinti darnumo poveikį portfelio grąžai. Siekiant disertacijoje užsibrėžto tikslo ir įgyvendinant uždavinius, pasitelktas statybos sektoriaus įmonės pavyzdys. Disertaciją sudaro įvadas, trys skyriai, bendrosios išvados, literatūros šaltinių sąrašas, autorės publikacijų disertacijos tema sąrašas. Įvade apta-riama tiriamoji problema, atskleidžiamas darbo aktualumas, aprašomas tyrimų objektas, formuluojamas darbo tikslas ir uždaviniai, aprašoma tyrimų metodika, išryškinamas mokslinis naujumas bei darbo praktinė reikšmė. Pirmame skyriuje analizuojamos projektų portfelio valdymo ir darnumo apibrėžtys, pateikiama išteklių paskirstymo bei projektų atrankos metodų, kriterijų ir modelių apžvalga, nagrinėjamas darnumo ir projektų portfelio valdymo ryšys. Antrame skyriuje teikiamos darnumo integravimo paskirstant finansinius išteklius projektų portfelyje teorinės prielaidos. Trečiame skyriuje aprašomas finansinių išteklių paskirstymo modelis, įvertinamas jo pritaikomumas. Disertacijos pabaigoje pateikiamos bendrosios viso darbo išvados. Disertacijos tema paskelbta 10 mokslinių straipsnių, perskaityti 6 pranešimai mokslinėse konferencijose

Exploring Factors Influencing Information Technology Portfolio Selection Process in Government-Funded Bioinformatics Projects

In 2012, the National Cancer Institute\u27s (NCI) Board of Scientific Advisors (BSA) conducted a review of the Center for Biomedical Informatics and Information Technology\u27s (CBIIT) bioinformatics program. The BSA suggested that the lack of a formal project selection process made it difficult to determine the alignment of projects with the mission of the organization. The problem addressed by this study was that CBIIT did not have an in-depth understanding of the project selection process and the factors influencing the process. The purpose of this study was to understand the project selection process at CBIIT. The research methodology was an exploratory case study. The data collection process included a phenomenological interview of 25 managers from program management, engineering, scientific computing, informatics program, and health sciences. The data analysis consisted of coding for themes, sensitizing, and heuristic coding, supported by a theoretical framework that included the technology acceptance model, the program evaluation theory, and decision theory. The analysis revealed the need for formal project portfolio governance, the lack of a predefined project selection process, and that the decision-making process was circumstantial. The study also revealed six major themes that affected the decision-making process: the CBIIT mission, the organizational culture, leadership, governance, funding, and organizational change. Finally, the study fills the gap in the literature regarding the project selection process for government-funded initiatives in information technologies. This study may contribute to positive social change by improving the project selection process at CBIIT, allowing for the effective use of public funds for cancer informatics researchers