A Seeking Schedule Intelligence Through Project Data Discovery Vanhoucke, Mario. creator author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XXIII, 161 p. 40 illus., 29 illus. in color. online resource. Based on the shared journey of two researchers, this book explores enhancing algorithms for the resource-constrained project scheduling problem. It examines the search for and significance of project data from multiple, distinct perspectives. In the first part, the quest for project data is presented as a continuous exploration of the complexity of the resource-constrained project scheduling problem. This quest is pursued by solving this challenging problem with the aid of state-of-the-art algorithms from the literature, each time gaining a deeper understanding of its challenging nature. To provide insights into the problem’s complexity, project data is created, manipulated, and analyzed in depth to make current projects easier or harder to schedule. This challenging quest for project data has resulted in new project databases for academic research, new ways of testing future algorithms, and insights into how to improve future algorithms to solve this project scheduling problem with limited resources. In turn, the second part discusses the relevance of project data, demonstrating to the reader the importance of the academic research presented in the first part for the professional world. It shows how project data can be used to calibrate real project data, leading to improved decision-making, e.g. for project scheduling, forecasting, and risk analysis. The book extends a warm invitation to academics and practitioners alike, as fellow seekers of knowledge, to enhance their project management skills. Do We Have Enough Project Data? (Part 1) -- Do the Projects Exist in Reality? -- Do We Have Good Schedules for the Projects? -- Can We Solve Every Project Instance? -- Why Is the RCPSP So Difficult? (Part 1) -- Can We Make the Projects Easier? (Part 1) -- Why Is the RCPSP So Difficult? (Part 2) -- Can We Make the Projects Easier? (Part 2) -- How to Make the Project Data Practically Relevant? -- Do We Have Enough Project Data? (Part 2). by Mario Vanhoucke. Production management Project management Operations research Big data Algorithms Quantitative research Operations Management Project Management Operations Research and Decision Theory Big Data Algorithms Data Analysis and Big Data TS155-194 9783031715075 https://doi.org/10.1007/978-3-031-71507-5 https://doi.org/10.1007/978-3-031-71507-5 241110 20251030113306.0 978-3-031-71507-5