47 research outputs found
Evolutionary Algorithms for Resource Constrained Project Scheduling Problems
The resource constrained project scheduling problems (RCPSPs) are well-known challenging research problems that require efficient solutions to meet the planning need of many practical high-value projects. RCPSPs are usually solved using optimization problem-solving approaches. In recent years, evolutionary algorithms (EAs) have been extensively employed to solve optimization problems, including RCPSPs. Despite that numerous EAs have been developed for solving various RCPSPs, there is no single algorithm that is consistently effective across a wide range of problems. In this context, this thesis aims to propose a few new algorithms for solving different RCPSPs that include singular-resource and multiple-resource problems with single and multiple objectives.
In general, RCPSPs are solved with an assumption that its activities are homogeneous, where all activities require all resource types. However, many activities are often singular, requiring only a single resource to complete an activity. Even though the existing algorithms that were developed for multi-resource problems, can solve this RCPSP variant with minor modifications, they are computationally expensive because they include some unnecessary resource constraints in the optimization process. In this thesis, at first, a problem with singular resource and single objective is considered. A heuristic-embedded genetic algorithm (GA) has been proposed for solving this problem, and it's effectiveness has been investigated. To enhance the performance of this algorithm, three heuristics are proposed and integrated with it. As there are no test problems available for singular resource problems, new benchmark problems are generated by modifying the existing multi-resource RCPSPs test set. As compared with experimental results of one of the modified algorithms and an exact solver, it was shown that the proposed algorithm achieved a better quality of solution while requiring a significantly smaller computational budget.
The proposed algorithm is then extended to make it suitable for solving multi-resource cases with a single objective, which are known as traditional RCPSPs. A self-adaptive GA is developed for this problem. The proposed self-adaptive component of the algorithm selects an appropriate genetic operator based on their performance as the evolution progresses and increases. To judge the performance of this algorithm, small to large-scale problem instances have been solved from the PSP Library and the results are compared with state-of-the-art algorithms. Based on the experimental results, it was found that the proposed algorithm was able to obtain much better solutions than the non-self-adaptive GA. Furthermore, the proposed approach outperformed the state-of-the-art algorithms.
In practice, cost of some resources varies with the day of the week or specific days in the month or year. To consider these day dependent costs, a new cost function is developed that is integrated with the usual cost fitness function in a multi-objective version of RCPSPs. Completion time is considered as the second objective. A heuristic-embedded self-adaptive multi-objective GA is proposed for both singular and multi-resource problems. In this algorithm, the selection mechanism is based on crowding distance and a reference point. A customized mutation operator is also introduced. The experimental results show that the proposed variant, with reference points-based selection, outperformed the variant, with crowding distance-based selection.
In many situations, resource availability varies with time, such as time of the day and in some particular days. A dynamic multi-operators-based GA is proposed to deal with this variant. Along with the genetic operators, two local search methods are also included in the self-adaptive mechanism. The proposed approach has been validated using both large-scale singular and multi-resource problem instances with a single objective. Its experimental results demonstrate the efficiency of the proposed dynamic multi-operator-based approach.
In summary, the proposed algorithms can solve different variants of RCPSPs that cover a broad spectrum of project scheduling problems, with significantly less computational tim
Future Trends in Advanced Materials and Processes
The Special Issue “Future Trends in Advanced Materials and Processes” contains original high-quality research papers and comprehensive reviews addressing the relevant state-of-the-art topics in the area of materials focusing on relevant or innovative applications such as radiological hazard evaluations of non-metallic materials, composite materials' characterization, geopolymers, metallic biomaterials, etc
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
3-я Міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні аспекти (ICSF 2022) 24-27 травня 2022 року, м. Кривий Ріг, Україна
Матеріали 3-ої Міжнародної конференції зі сталого майбутнього: екологічні, технологічні, соціальні та економічні аспекти (ICSF 2022) 24-27 травня 2022 року, м. Кривий Ріг, Україна.Proceedings of the 3rd International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2022) 24-27 May 2022, Kryvyi Rih, Ukraine
LIPIcs, Volume 244, ESA 2022, Complete Volume
LIPIcs, Volume 244, ESA 2022, Complete Volum
Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року
Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року
Neolithic land-use in the Dutch wetlands: estimating the land-use implications of resource exploitation strategies in the Middle Swifterbant Culture (4600-3900 BCE)
The Dutch wetlands witness the gradual adoption of Neolithic novelties by foraging societies during the Swifterbant period. Recent analyses provide new insights into the subsistence palette of Middle Swifterbant societies. Small-scale livestock herding and cultivation are in evidence at this time, but their importance if unclear. Within the framework of PAGES Land-use at 6000BP project, we aim to translate the information on resource exploitation into information on land-use that can be incorporated into global climate modelling efforts, with attention for the importance of agriculture. A reconstruction of patterns of resource exploitation and their land-use dimensions is complicated by methodological issues in comparing the results of varied recent investigations. Analyses of organic residues in ceramics have attested to the cooking of aquatic foods, ruminant meat, porcine meat, as well as rare cases of dairy. In terms of vegetative matter, some ceramics exclusively yielded evidence of wild plants, while others preserve cereal remains. Elevated δ15N values of human were interpreted as demonstrating an important aquatic component of the diet well into the 4th millennium BC. Yet recent assays on livestock remains suggest grazing on salt marshes partly accounts for the human values. Finally, renewed archaeozoological investigations have shown the early presence of domestic animals to be more limited than previously thought. We discuss the relative importance of exploited resources to produce a best-fit interpretation of changing patterns of land-use during the Middle Swifterbant phase. Our review combines recent archaeological data with wider data on anthropogenic influence on the landscape. Combining the results of plant macroremains, information from pollen cores about vegetation development, the structure of faunal assemblages, and finds of arable fields and dairy residue, we suggest the most parsimonious interpretation is one of a limited land-use footprint of cultivation and livestock keeping in Dutch wetlands between 4600 and 3900 BCE.NWOVidi 276-60-004Human Origin
Taphonomy, environment or human plant exploitation strategies?: Deciphering changes in Pleistocene-Holocene plant representation at Umhlatuzana rockshelter, South Africa
The period between ~40 and 20 ka BP encompassing the Middle Stone Age (MSA) and Later Stone Age (LSA) transition has long been of interest because of the associated technological change. Understanding this transition in southern Africa is complicated by the paucity of archaeological sites that span this period. With its occupation sequence spanning the last ~70,000 years, Umhlatuzana Rock Shelter is one of the few sites that record this transition. Umhlatuzana thus offers a great opportunity to study past environmental dynamics from the Late Pleistocene (MIS 4) to the Late Holocene, and past human subsistence strategies, their social organisation, technological and symbolic innovations. Although organic preservation is poor (bones, seeds, and charcoal) at the site, silica phytoliths preserve generally well throughout the sequence. These microscopic silica particles can identify different plant types that are no longer visible at the site because of decomposition or burning to a reliable taxonomical level. Thus, to trace site occupation, plant resource use, and in turn reconstruct past vegetation, we applied phytolith analyses to sediment samples of the newly excavated Umhlatuzana sequence. We present results of the phytolith assemblage variability to determine change in plant use from the Pleistocene to the Holocene and discuss them in relation to taphonomical processes and human plant gathering strategies and activities. This study ultimately seeks to provide a palaeoenvironmental context for modes of occupation and will shed light on past human-environmental interactions in eastern South Africa.NWOVidi 276-60-004Human Origin