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Healthcare operations, in hospitals and home healthcare settings, are inundated with complex fuzzy features that impose difficulties in the creation of work schedules. As healthcare workers call for schedules that accommodate their individual preferences and patients continue to call for more personalized healthcare, further research into multi-cri
Many Healthcare providers have suffered a crisis of poor quality and inefficiency with rapidly increasing costs. Healthcare delivery faces complex scheduling needs and stands to gain from advances in scheduling technology and understanding. This special issue presents some new progress in applying scheduling techniques to several real-life problems in healthcare delivery.
Uncertainties in project management can make scheduling and resource allocation difficult. To overcome some of the limitations of a heuristic method of unconstrained scheduling problems, a new resource allocation technique is presented as a way to account for and incorporate uncertainties into scheduling. Using this fuzzy set theory technique, resources are allocated to minimize unavoidable project delays, utilize available resources, and reduce resource interruptions. Three criteria are used to measure performance compared to the Minimum Late Finish (MINLFT) and the Minimum Slack (MINSLK) rules: project duration, resource utilization, and resource interruption. 51 cases were studied from the literature. The proposed method produced 25 solutions which satisfied all three objectives simultaneously, a number that is about 60 percent higher than the MINLFT and MINSLK rules. A framework for performing resource allocation in an uncertain environment is provided, along with an outline of the two major steps of this technique: Group Formation and Group Evaluation.
This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms. Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.
The book reports on advanced theories and methods in two related engineering fields: electrical and electronic engineering, and communications engineering and computing. It highlights areas of global and growing importance, such as renewable energy, power systems, mobile communications, security and the Internet of Things (IoT). The contributions cover a number of current research issues, including smart grids, photovoltaic systems, wireless power transfer, signal processing, 4G and 5G technologies, IoT applications, mobile cloud computing and many more. Based on the proceedings of the first International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM 2016), held in Voila Bagatelle, Mauritius from November 25 to 27, 2016, the book provides graduate students, researchers and professionals with a snapshot of the state-of-the-art and a source of new ideas for future research and collaborations.
Knowledge management (KM) has become an important business strategy in an era of accelerated globalization, digitalization, and servitization of products and services. Maximizing the use of organizational resources becomes fundamental for continuous growth and prosperity. Organizations of various kinds such as resource-based organizations, product-based organizations, as well as knowledge-intensive service-oriented organizations require specific policies and support services to improve the knowledge management in their respective organizations. Knowledge Management Strategies and Applications focuses on the way organizations can create knowledge, share existing or new knowledge, and disseminate them among the stakeholders, most importantly among the employees, managers, customers, and suppliers. The selected topics are drawn from several fields of studies and give a multidisciplinary outlook. The book will be interesting not only for the researchers and students but also for the managers who want to improve knowledge sharing and innovation capabilities in their organizations.
Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with adaptive perturbations, for a nurse scheduling problem arising at a major UK hospital. The main idea behind this technique is to decompose a schedule into its components (i.e. the allocated shift pattern of each nurse), and then mimic a natural evolutionary process on these components to iteratively deliver better schedules. The worthiness of all components in the schedule has to be continuously demonstrated in order for them to remain there. This demonstration employs a dynamic evaluation function which evaluates how well each component contributes towards the final objective.Two perturbation steps are then applied: the first perturbation eliminates a number of components that are deemed not worthy to stay in the current schedule; the second perturbation may also throw out, with a low level of probability, some worthy components. The eliminated components are replenished with new ones using a set of constructive heuristics using local optimality criteria. Computational results using 52 data instances demonstrate the applicability of the proposed approach in solving real-world problems.
This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001. The 45 revised full papers presented were carefully reviewed and selected from a total of 87 submissions. Also included are two tutorial surveys and two invited papers. The book is organized in topical sections on algorithm improvements, performance assessment and comparison, constraint handling and problem decomposition, uncertainty and noise, hybrid and alternative methods, scheduling, and applications of multi-objective optimization in a variety of fields.