Project Management Support Research Articles

Evaluation model design of project construction safety level based on bidirectional recurrent neural network (BiRNN) and bidirectional long short-term memory (BiLSTM)

Integrating deep learning methods for multi-element regression analysis poses a challenge in constructing safety evaluations for building construction. To address this challenge, this paper evaluates the integration of construction safety by quantitatively analyzing practitioners’ information and on-site construction conditions. The analytic hierarchy process (AHP) method quantifies construction safety capabilities, considering four key aspects: operators’ primary conditions, organizational personnel’s working conditions, on-site management conditions, and analysis of unsafe behaviors. A comprehensive set of 19 secondary causal factors is constructed. Furthermore, a hybrid model based on bidirectional recurrent neural network (BiRNN) and bidirectional long short-term memory (BiLSTM) is developed for construction safety evaluation, enhancing the model’s generalization ability by introducing the Dropout mechanism. Experimental results demonstrate that the fusion of BiRNN and BiLSTM methods outperforms traditional methods in construction safety evaluation, yielding mean squared error (MSE) and root mean squared error (RMSE) values of 0.48 and 0.69 and mean absolute error (MAE) and mean absolute percentage error (MAPE) values of 0.54 and 3.36%, respectively. The case study affirms that BiRNN-BiLSTM can accurately identify potential safety risks, providing reliable decision support for project management.

Interdisciplinary perspective on architectural programming: current status and future directions

PurposeArchitectural programming, as a critical phase in construction projects, has been widely recognized for its importance and advantages throughout the construction process. With the rapid development of the socioeconomic landscape, architectural programming has garnered increasing attention from various other disciplines, becoming a key trend in interdisciplinary collaboration. This study aims to provide a comprehensive understanding of the current status and future directions of architectural programming from an interdisciplinary perspective through scientometric analysis and systematic review.Design/methodology/approachThis study first collected English journal articles on architectural programming published between 1975 and 2024 from the Web of Science and Scopus databases. After an initial screening of titles and abstracts, 515 articles were selected for scientometric analysis to reveal the current state and advantages of architectural programming research in multidisciplinary fields. Subsequently, a second screening of full-text articles identified 75 journal articles for systematic review, focusing on research topics and challenges in interdisciplinary applications.FindingsThe study reveals an exponential increase in the number of papers related to architectural programming between 1975 and 2024, particularly in the last decade. Six key research topics of architectural programming in multidisciplinary fields were identified: (1) performance optimization and evaluation, (2) digitalization and automation development, (3) project management and decision support, (4) improvement of human and social welfare, (5) sustainable resources and environment and (6) educational practices of architectural programming. Additionally, the study identified the main challenges in the interdisciplinary application of architectural programming, including (1) incompatibility among disciplines, (2) limitations of data and methodologies and (3) insufficient social engagement. To address these challenges, three potential future directions were proposed: (1) establishing interdisciplinary teams and platforms, (2) enhancing multi-source data integration and digital transformation and (3) improving governance mechanisms and educational training.Originality/valueBy combining quantitative and qualitative methods, this study provides a comprehensive review of architectural programming research and applications in multidisciplinary fields, offering theoretical foundations and practical references for the future development of architectural programming. This review not only aids in understanding the overall status of current architectural programming research but also offers valuable insights and recommendations for future research directions and practical applications.

Improving ambulatory patient access through strategic reorganisation and implementation of innovative ambulatory care best practices

John Muir Health, a large health system in northern California, struggled with a complex practice management structure that lacked role clarity and core positions, making it difficult to bring about positive change within the ambulatory setting. As part of a broader, strategic partnership to improve operations and deliver healthcare, health system leaders partnered with Optum Advisory to reorganise the practice management structure and optimise primary care patient access. Across its duration, the partnership improved access within primary care while reducing the administrative burden on providers through care team redesign, and with a new structure, physicians received administrative clarity and practice managers have leaders providing support for access, project management and innovation. These changes led to greater innovation and efficiency, resulting in higher satisfaction for patients, providers and staff. Optimising access and productivity, John Muir Health primary care practices have decreased the amount of time it takes for patients to get into the practice, increasing the overall number of patients they have been able to see. In addition, centralised prescription refills have allowed patients to receive their medications quicker while enabling physicians to concentrate on direct patient care. The overall result has been less administrative burden for providers and staff, allowing for more top-of-licence work and time with patients.

Construction Method and Practical Application of Oil and Gas Field Surface Engineering Case Database Based on Knowledge Graph

To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent search and recommendations. The article leverages Optical Character Recognition (OCR) technology, knowledge graph technology, and Natural Language Processing (NLP) technology. It explores the mechanisms for classifying construction cases, methods for constructing a case database, structuring case data, intelligently retrieving and matching cases, and intelligent recommendation methods. This research forms a complete, feasible, and scalable method for deconstructing, storing, intelligently retrieving, and recommending construction cases, providing a theoretical basis for the establishment of a construction case database. It aims to meet the needs of digital project management and intelligent decision-making support in the oil and gas sector, thereby enhancing the efficiency and accuracy of project construction. This work offers a theoretical foundation for the development of an intelligent management platform for ground engineering projects in the oil and gas industry, supporting the sector’s digital transformation and intelligent development.

METHODOLOGICAL PRINCIPLES OF THE FORMATION OF STRATEGIC CONTROL IN THE CONDITIONS OF DIGITALIZATION OF THE ENTERPRISE DEVELOPMENT MANAGEMENT SYSTEM

The article formulates the methodological principles of the formation of strategic controlling in the conditions of digitalization of the economy. The paper proposes a systematic approach to the formation of methodological principles for the application of strategic controlling in the conditions of digitization of the enterprise development management system. The relationship between strategic controlling and the general factors of successful strategies is revealed, and a general diagram of the relationship between strategy and strategic controlling is presented. It is noted that strategic management control is located at the intersection of innovation management, investment management, project management, information and analytical support, management accounting and performs the function of "management by deviation". Digitization is a change in the business model based on digital technologies, and not just a replacement of analog resource to digital. Strategic controlling, as a system of providing organizational, methodological, informational and analytical management, is able to ensure system changes and feedback in the management circuit with the greatest efficiency. He is able to determine the direction and speed of development, to investigate the peculiarities of the external and internal environment, to economically substantiate such transformations in all functional subsystems of the enterprise. Digitization affects the market and changes professions. The successful construction and development of strategic controlling in the company requires the support of top management and qualified controllers, a corporate culture in which dialogue is possible. The factors affecting the implementation of strategic controlling in the organization are revealed. Digitization is a basic element in the proposed methodological approach to the application of strategic controlling in enterprise management.

514 Rapid Activation Trial (RAT) Program for High Priority Clinical Trials

OBJECTIVES/GOALS: Mayo Clinic (MC) launched the Rapid Activation Trial (RAT) pilot program in 2022 to expedite the activation of high priority and high impact clinical trials. The objective was to develop a process for rapid activation through robust screening, prioritization, and project management (PM) support. METHODS/STUDY POPULATION: The project team developed a robust screening and approval process for the RAT program using a combination of an objective scoring tool (based on strategic priorities) and a diverse selection committee to screen and approve eligible trials. Sponsors had to commit to RAT program timelines. Upon approval, trials were prioritized at the highest level within each business unit involved in the activation process. The number of trials approved annually were limited to 8 to manage volume and facilitate seamless prioritization with an activation timeline goal of 6 weeks. Project management support for RAT program focused on financial, regulatory, logistical, and operational elements to open trials expeditiously. RESULTS/ANTICIPATED RESULTS: In 2022, thirteen (13) applications were received and eight (8) were approved by the RAT selection committee. The approved trials activated with a median open to enrollment time of 6.4 weeks from engaging with business units. They also aligned closely with organization’s strategic priorities, including but not limited to Investigator Initiated Trials, Multi-Site protocols, IND/IDE protocols, Rare Diseases, First in Human and Commercialization potential trials. PI and study team feedback was positive. In 2023, the RAT program was renewed due to the pilot’s significant success in 2022. The goal is to open 10 trials and 5 have been activated by the end of Q3, 2023 with a median timeline of 6 weeks. DISCUSSION/SIGNIFICANCE: Rapid activation of high priority and high impact clinical trials enables an organization to strategically prioritize and open complex clinical trials. This allows the delivery of innovative, timely cures to patients in an expeditious timeline.

74 Trial-CARE: Centralized Support Services for Investigator-Initiated Multi-Site Clinical Trials

OBJECTIVES/GOALS: To describe the impact of Trial-CARE (Coordination, Acceleration, and Recruitment Enhancement), a centralized service core at Washington University (WU), aimed at enhancing the capability of investigator-initiated multi-site clinical trials at WU and partner CTSA institutions. METHODS/STUDY POPULATION: Through review of our marketing materials and service tracking system we defined the following Trial-CARE offerings: Infrastructure: Trial-CARE is a centralized service core at WU. Whereby, a team member is sourced to an investigator-initiated multi-site clinical trial (II-MCT) to ensure the achievement of study milestones across any phase of the clinical trial life cycle. Team: Our team consists of research professionals with expertise in II-MCT project management, data management, and administrative/regulatory management. Services: * One free 60-minute case consultation * Tiers of Service * Academic Research Organization (ARO) support * Clinical Coordinating Center * Data Coordinating Center * II-MCT project management support * Time-limited targeted support RESULTS/ANTICIPATED RESULTS: Trial-CARE has completed 94 consultations in support of WU and partner CTSA institutions enabling the streamlining of study start-up; guidance for study recruitment, implementation, and operations; and offering resources to foster career development. Consultations can be completed at any phase in the clinical trial lifecycle, with Trial-CARE completing: * 12% in the idea phase * 45% in the grant development and submission stage * 28% after funding has been awarded Top reasons researchers connect with Trial-CARE about II-MCTs: * regulatory guidance (40%) * general information about Trial-CARE Services and II-MCTs (35%) * protocol development (21%) * data management (20%) * study budgeting (20%) DISCUSSION/SIGNIFICANCE: In response to a WU wide survey, Trial-CARE plans to generate informational webinars and is creating a clinical trial tracking dashboard, to pro-actively offer support services to researchers prior to grant funding. The goal is also to increase the percentage of consultations completed in the idea phase and the grant development and submission stage.

Multi-objective planning for time-cost trade-offs in multi-project parallel environment

PurposeProject managers bear the responsibility of selecting and developing resource scheduling methods that align with project requirements and organizational circumstances. This study focuses on resource-constrained project scheduling in multi-project environments. The research simplifies the problem by adopting a single-project perspective using gain coefficients.Design/methodology/approachIt employs uncertainty theory and multi-objective programming to construct a model. The optimal solution is identified using Matlab, while LINGO determines satisfactory alternatives. By combining these methods and considering actual construction project situations, a compromise solution closely approximating the optimal one is derived.FindingsThe study provides fresh insights into modeling and resolving resource-constrained project scheduling issues, supported by real-world examples that effectively illustrate its practical significance.Originality/valueThe research highlights three main contributions: effective resource utilization, project prioritization and conflict management, and addressing uncertainty. It offers decision support for project managers to balance resource allocation, resolve conflicts, and adapt to changing project demands.

Interaction mechanisms of interface management risks in complex systems of high-speed rail construction projects: an association rule mining-based modeling framework

PurposeThis study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.Design/methodology/approachThis paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.FindingsThe results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.Originality/valueThe interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.

Proposal for A Model Based on Elements and Digital Transformation Project Management Practices to Support Business Agility

Objective: The objective of this article is to present a conceptual model that includes the elements and practices of Digital Transformation project management to support Business Agility, as the adoption of project management practices and digital technologies allows organizations to adapt flexibly to the business environment in which they operate. Method/design/approach: To achieve the objective, field research was carried out using interviews and focus groups. Results and conclusions: Based on the results, it was possible to present a conceptual model that represents the elements and practices of managing Digital Transformation projects to support Business Agility in organizations. Research Contributions: In relation to theoretical contributions, the results obtained from the literature review compared with empirical research allowed discussions to advance on the phenomenon of Digital Transformation and Business Agility. Originality/Value: A practical model capable of supporting project management professionals during the life cycle of Digital Transformation projects stands out.

A framework for project management software tool selection

Projects play a fundamental role in improving firms’ performance. This is moderated by firms’ ability to manage projects as well as on available methods and tools supporting project management. Many software tools exist in the market today, to meet different levels of requirements and offer various functionalities. Thus, there is a need to support the decision of project managers in terms of selecting the most suitable tool to use for their projects. This paper aims to provide a framework to support the comparison and the selection of project management software tools. A comprehensive list of functionalities to select software tools as well as a scoring system were specified. A prototypical implementation is presented to gain insights into framework comprehensiveness and practicality. The framework is expected to assist project managers in selecting the most suitable tools considering project context and stakeholders requirements.

Using Trend Modelling to Support Project Scheduling, Management and Prediction

Using Trend Modelling to Support Project Scheduling, Management and Prediction

Job relevance or perceived usefulness? What features of immersive virtual reality software predict intention to use in a future project-based-learning scenario: a mixed method approach

Not only since COVID-19, the topic of decentralized working and learning methods is becoming increasingly important for various reasons. New virtual reality technologies enable learning in immersive scenarios, which is good when learning from home is advised. However, not all immersive Virtual Reality (iVR) training incorporates learning systems that support complex, realistic, practical tasks that lead to a product or enable acquiring knowledge and life-enhancing skills like project-based learning. Although there are many iVR applications available that support project management, the specific features of these applications that lead to the intention to use (and therefore life-enhancing skills) have yet to be discovered. In this exploratory mixed-method study, we investigated the question of the importance of perceived usefulness (PU) and job relevance (JR) as predictors of intention to use (ItU) in a selection of immersive iVR application features. We started with market research and aggregated 88 software features in 13 categories of 34 professional iVR applications. After an expert selection and ranking procedure, a survey was developed. After deriving from the TAM 2 model and with a sample n = 103, we computed the relationship of JR, PU, and ItU. Although high values were generally observed, we found that the importance of PU is higher than JR when it comes to ItU. Limitations of the study are discussed, and suggestions for further research are given.

Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study.

The narrative free-text data in electronic medical records (EMRs) contain valuable clinical information for analysis and research to inform better patient care. However, the release of free text for secondary use is hindered by concerns surrounding personally identifiable information (PII), as protecting individuals' privacy is paramount. Therefore, it is necessary to deidentify free text to remove PII. Manual deidentification is a time-consuming and labor-intensive process. Numerous automated deidentification approaches and systems have been attempted to overcome this challenge over the past decade. We sought to develop an accurate, web-based system deidentifying free text (DEFT), which can be readily and easily adopted in real-world settings for deidentification of free text in EMRs. The system has several key features including a simple and task-focused web user interface, customized PII types, use of a state-of-the-art deep learning model for tagging PII from free text, preannotation by an interactive learning loop, rapid manual annotation with autosave, support for project management and team collaboration, user access control, and central data storage. DEFT comprises frontend and backend modules and communicates with central data storage through a filesystem path access. The frontend web user interface provides end users with a user-friendly workspace for managing and annotating free text. The backend module processes the requests from the frontend and performs relevant persistence operations. DEFT manages the deidentification workflow as a project, which can contain one or more data sets. Customized PII types and user access control can also be configured. The deep learning model is based on a Bidirectional Long Short-Term Memory-Conditional Random Field (BiLSTM-CRF) with RoBERTa as the word embedding layer. The interactive learning loop is further integrated into DEFT to speed up the deidentification process and increase its performance over time. DEFT has many advantages over existing deidentification systems in terms of its support for project management, user access control, data management, and an interactive learning process. Experimental results from DEFT on the 2014 i2b2 data set obtained the highest performance compared to 5 benchmark models in terms of microaverage strict entity-level recall and F1-scores of 0.9563 and 0.9627, respectively. In a real-world use case of deidentifying clinical notes, extracted from 1 referral hospital in Sydney, New South Wales, Australia, DEFT achieved a high microaverage strict entity-level F1-score of 0.9507 on a corpus of 600 annotated clinical notes. Moreover, the manual annotation process with preannotation demonstrated a 43% increase in work efficiency compared to the process without preannotation. DEFT is designed for health domain researchers and data custodians to easily deidentify free text in EMRs. DEFT supports an interactive learning loop and end users with minimal technical knowledge can perform the deidentification work with only a shallow learning curve.

AUTOMATED PROJECT MANAGEMENT SYSTEM IN TRANSPORT LOGISTICS

The article is a continuation of regular research on project management based on efficient transportation. The purpose of the work is to improve the efficiency of management decision-making in the implementation of projects in transport logistics through the use of automated planning and analysis systems. The object of study is the process of forming organizational support for project management in transport logistics using automated planning and analysis systems for project efficiency. The subject of the study is the practical tools for organizational support of project management in transport logistics using automated systems for planning and analyzing project performance. Methods. In the course of the study, a systematic approach was implemented, general scientific methods were used, including logical analysis, synthesis, induction, deduction, analogy, and modeling. The theoretical and methodological basis of the study is the fundamental provisions of project management, management efficiency theory, scientific works of domestic and foreign scientists on project management at the micro, meso, and macro levels. Given the purpose of the work, several tasks were set and solved, in particular, the applied imperatives of resource and budget planning were outlined on the example of a logistics center based on the Odesa seaport and the project implementation was monitored in Microsoft Project. In terms of resource and budget planning, the expediency of using the method and indicators of the volume utilized is proved. The actual progress of the project against the planned indicators is analyzed. A new project was created using the Microsoft Project software and data entry method. In terms of monitoring, conclusions were drawn on the course of events in the project implementation and the status of implementation by individual types of work was clearly shown. All this made it possible to achieve concrete results. In terms of resource and budget planning, it was determined to what extent there is a deviation from the planned project implementation timeframe. In terms of monitoring, the need to optimize staffing, budget, and time parameters was identified. The essence of this optimization boils down to the decision to attract additional labor resources with the corresponding cost of work per hour. This made it possible to get rid of the conflict and obtain positive dynamics in the project implementation, as evidenced by the date of its completion, which remained unchanged after the resources were equalized. The need to continue the study and focus on project risk management is outlined.

Does Digitalization Supports Project Management Effectiveness? New Insight on the Role of Intellectual Capital

The challenges of the fourth industrial revolution faced by project managers are not only related to continuous adaptation to new technologies and the application of the optimal technical solution within each project but also imply the implementation of systemic changes in project management practice. There is no clear evidence in the literature about project management effectiveness in the digital economy or readiness for digital transformation in project-oriented organizations. The purpose of this paper is to identify the influence of intellectual capital components on project management effectiveness in the context of changes that are stimulated by digitalization, as well as the indirect impact of the company’s readiness for digital transformation. Using 147 fully matched pairs of questionnaires collected from project managers and end-users of construction projects, it is proven that digital transformation readiness is relevant as a mediator and moderator between intellectual capital components and project management effectiveness. The contribution of this research is reflected in highlighting the importance of assessing project management effectiveness in order to assure project success. The digital transformation readiness of project-oriented organizations is an important element for increasing project team motivation, building trust, and developing effective communication channels.

A Review-Trade off Time-Cost-Quality by Genetic Algorithm

Abstract: Project success is measured in terms of time, money, and quality. As a result, they are regarded as the most significant goals in construction projects. Project managers must complete their work on schedule, on budget, and to a high standard of quality. Project managers introduce a variety of approaches to achieve these contradictory goals. For each activity in the project, there are different modes of execution. The goal of this research is to propose an optimization model that can be used to support project managers and decision makers in completing this difficult work, which leads to the selection of the best candidate’s solution. The developed model is based on Genetic Algorithms, which offer numerous benefits over older methods. Optimization strategies and are thought to be suitable for many goal functions. Genetic engineering has been developed. The target function, design variables impacting that target, and problem limitations are all included in the algorithms model. The model's viability is tested by applying it to two projects. The findings suggest that the proposed method is effective technique can assist practitioners in assessing several modes of activity and quickly determining the lowest cost. A deadline for the project that meets the quality requirements. The model can quickly find the optimal solution from a large number of options. A large number of solutions in a fair amount of time Furthermore, the results show that the current strategy can be employed in the creation of a set of optimal solutions.

Examining the critical success factors related to enterprise resource planning: a case study in Ordu province

Enterprise Resource Planning (ERP) and success factors are systems that enable effective and efficient management of businesses by facilitating coordination and interaction among different units. Therefore, the decision to select the right and applicable ERP implementation and success factors for businesses is a crucial matter. However, due to the cost of ERP implementations and the lengthy adaptation periods for businesses, selecting the relevant systems and success factors requires careful consideration. Identifying ERP implementations and success factors that are suitable for the business processes and structure of the company is a significant decision-making problem, which can be considered as a gap in the literature. In this regard, this study used the Neutrosophic Decision Making Trial and Evaluation Laboratory (DEMATEL) method to analyze the critical success factors for ERP in production companies that had more than 10 employees. The results show that project management and top management support were the most important factors. The results have significant implications for business managers and stakeholders involved in the subject matter in terms of cost and resource efficiency as well as gaining competitive advantage.

P67 Overall lifetime risk for alopecia areata is 2.1% and is higher in women, non-White ethnic groups and the most deprived: a UK population-based cohort study

Abstract Alopecia areata (AA) is an immune-mediated nonscarring alopecia often associated with substantial morbidity. However, there are limited population-based data on potential disparities in the burden of AA, including across different ethnicities and sociodemographic classifications. We aimed to provide the first large-scale, population-based evaluation of lifetime risk of AA across sociodemographic subgroups. This study used routinely collected data from a large UK population-based database: the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). All children and adults registered with general practices contributing to the RCGP RSC network in the period 2009–2018 without a prior diagnosis of AA were included. People were considered to develop AA if they had an AA diagnosis and, in the subsequent 365 days, no code for an alternative diagnosis (e.g. traction alopecia and scarring alopecia). The cumulative lifetime risk of AA was estimated at age 80 years using survival models, with age as the timescale and accounting for the competing risk of death. Lifetime risk was calculated for the whole population and by sociodemographic subgroups comprising sex, major UK ethnicity groups and socioeconomic deprivation. In a total population of 4 052 231, 6961 developed new-onset AA. The lifetime risk in the overall population was 2.11% [95% confidence interval (CI) 2.06–2.16]. There was substantial difference in lifetime risk of AA by ethnicity; lifetime risk was 1.74% (95% CI 1.68–1.80) in the White subgroup, 5.87% (95% CI 5.51–6.24) in Asian, 3.03% (95% CI 2.63–3.42) in Black, 4.44% (95% CI 3.50–5.37) in mixed and 4.47% (95% CI 3.63–5.31) in other ethnic groups. Females had a higher lifetime risk of AA than males: 2.35% (95% CI 2.28–2.43) vs. 1.88% (95% CI 1.81–1.94). Lifetime risk was greater with increasing socioeconomic deprivation: least-deprived 1.68% (95% CI 1.59–1.78) vs. most-deprived quintile 2.92% (95% CI 2.77–3.07). Our findings demonstrate that AA affects nearly 1 in 50 people over a lifetime. Lifetime risk is substantially greater in people of non-White ethnicity and is highest in those of Asian ethnicity (one in 17 people). The lifetime risk is also higher in females and those with the greatest socioeconomic deprivation. Clinicians should be aware of the disproportionate distribution of AA across the population and support the provision of healthcare resource to groups with the highest burden. Funding sources: this research was sponsored by Pfizer. Project management, medical writing and statistical support were provided by Momentum Data, UK, and were funded by Pfizer.

A reactive scheduling approach for the resource-constrained project scheduling problem with dynamic resource disruption

PurposeThis paper aims to develop an algorithm to study the impact of dynamic resource disruption on project makespan and provide a suitable resource disruption ratio for various complex industrial and emergency projects.Design/methodology/approachThis paper addresses the RCPSP in dynamic environments, which assumes resources will be disrupted randomly, that is, the information about resource disruption is not known in advance. To this end, a reactive scheduling model is proposed for the case of random dynamic disruptions of resources. To solve the reactive scheduling model, a hybrid genetic algorithm with a variable neighborhood search is proposed.FindingsThe results obtained on the PSLIB instances prove the performance advantage of the algorithm; through sensitivity analysis, it can be obtained, the project makespan increases exponentially as the number of disruptions increase. Furthermore, if more than 50% of the project's resources are randomly disrupted, the project makespan will be significantly impacted.Originality/valueThe paper focuses on the impact of dynamic resource disruptions on project makespan. Few studies have considered stochastic, dynamic resource uncertainty. In addition, this research proposes a reasonable scheduling algorithm for the research problem, and the conclusions drawn from the research provide decision support for project managers.