This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. (...) Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance and spacing of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness. (shrink)

Based on the concept of “passengers self-help hubbing,” we build a flight schedule optimization model where maximizing the number of feasible flight connections, indicating transfer opportunities, as one objective and minimizing total slot displacements as the other objective. At the same time, the “Demand Smoothing Model” is introduced into the flight schedule optimization model to reduce the queuing delays for arrival and departure flights. We take into account all aircraft itineraries, the difficulty level of schedule coordination, and the maximum displacement (...) of any single flight acceptable to airlines when optimizing flight schedule. Given an original schedule, the model produces a feasible modified schedule that obeys the slot limits specified for an airport without canceling any flights, increases transfer opportunities, and improves on-time performance for hub airports while reducing interference with airline scheduling preferences. The model was verified with the operating data of the Urumqi international airport, and the results show that minor adjustments to flight schedules can increase the transfer opportunities of the airport and significantly reduce flight queuing delays. (shrink)

Eventualities and worlds are analysed uniformly as schedules of certain descriptions of eventuality-types (reversing the reduction of eventuality-types to eventualities). The temporal interpretation of modals in Condoravdi 2002 is reformulated to bring out what it is about eventualities and worlds that is essential to the account. What is essential, it is claimed, can be recovered from schedules that may or may not include worlds.

This comment on Michael Bratman's Planning and the Stability of Intention focuses on sources of the rational stability of intentions which are not related to the presence of reflectively overrideable non-deliberative habits of (non)reconsideration. It is true that intentions have a rational resistance to reconsideration, but this stability can be understood as a by-product of the scheduling of cognitive tasks. This scheduling effect is intrinsic to all actual systems, that is, systems whose reasoning is not instantaneous or otherwise (...) costless. Additionally, rules governing practical reasoning, including rules governing reasoning with intentions, will not uniformly be subject to overrides resulting from reflective operations. Hence there is no basis for distinguishing human reasoners from artificial reasoners by reference to an alleged human capacity to reflectivity evaluate its own reasoning operations. (shrink)

The COVID-19 pandemic has driven organizations to implement various flexible work arrangements. Due to a lack of longitudinal studies, there is currently no consensus in specialized literature regarding the consequences of flexible work arrangements on employee mental health, as well any long term potential impacts. Using the Job Demand-Resource Model, this study documents consequences of the implementation of two types of flexible work arrangement: work schedule flexibility and teleworking on employee mental health over time, and the mediating role played by (...) work overload during the accelerated implementation of flexible work arrangements in the course of the COVID-19 pandemic. Using a longitudinal design and probabilistic sampling, 209 workers participated in this study, twice answering a flexible work arrangement and mental health questionnaire during the pandemic. Findings of this moderated-mediation suggest that work schedule flexibility generates positive effects on mental health over time due to decreased work overload, but only for employees not working from home. These results offer theoretical and practical implications applicable to organizations considering implementation of flexible work arrangements, particularly with regard to how these flexible practices could support a balance between demand and resources, their impact on work overload, and employee mental health over time. (shrink)

Smart city is a brand-new city form, in which information and communication technologies are utilized to sense, analyze, and integrate the key information of city operation core system, so that intelligent responses can be immediately and effectively taken to various demands including people’s livelihood, environmental protection, public safety, city services, and industrial and commercial activities. Digital economy is a mixed economy with the coexistence of multiple business models and diversified value creation models based on the information and communication technologies and (...) in the digital economy, many things are undergoing huge changes, and their corresponding economic rules also need to be adjusted. On the basis of analyzing previous research works, this paper expounded the research status and significance of smart city’s resource scheduling and strategic management, elaborated the development background, current status, and future challenges of digital economy, introduced the methods and principles of city-level spatiotemporal data model and spatial full factor coding, formulated resource scheduling strategies for smart city based on digital economy, explored the dynamic fusion, storage, and update of smart city’s multisource heterogeneous data, conducted the information display and analysis of multilevel smart city, proposed strategic management approaches for smart city based on digital economy, analyzed the integrated implementation model of shared resource scheduling and people-oriented social management, and discussed the economic growth factors and standardization mechanism of smart city under the background of digital economy. The results of this study provide a reference for further research studies on the resource scheduling and strategic management of smart city under the background of digital economy. (shrink)

Emergency scheduling of public resources on the cloud computing platform network can effectively improve the network emergency rescue capability of the cloud computing platform. To schedule the network common resources, it is necessary to generate the initial population through the Hamming distance constraint and improve the objective function as the fitness function to complete the emergency scheduling of the network common resources. The traditional method, from the perspective of public resource fairness and priority mapping, uses incremental optimization algorithm (...) to realize emergency scheduling of public resources, neglecting the improvement process of the objective function, which leads to unsatisfactory scheduling effect. An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. Experimental results show that the proposed method can effectively improve the efficiency of emergency resource scheduling, and the reliability of emergency scheduling is better. (shrink)

The integrated scheduling algorithm of process sequence time-selective strategy is an advanced algorithm in the field of integrated scheduling. The proposed algorithm points out the shortcomings of the process sequence time-selective strategy. Generally, there are too many “trial scheduling” times. The authors propose that there is no need to make “trial scheduling” at every “quasi-scheduling time point.” In fact, the process scheduling scheme can be obtained by trial scheduling on some “quasi-scheduling time (...) points.” The scheduling result is the same as that of the sequence timing strategy. The proposed algorithm reduces the runtime of scheduling algorithm and improves the performance of the algorithm without reducing the optimization effect. (shrink)

This paper addresses a variant of the job shop scheduling problem with total tardiness minimization where task durations and due dates are uncertain. This uncertainty is modelled with intervals. Different ranking methods for intervals are considered and embedded into a genetic algorithm. A new robustness measure is proposed to compare the different ranking methods and assess their capacity to predict ‘expected delays’ of jobs. Experimental results show that dealing with uncertainty during the optimization process yields more robust solutions. A (...) sensitivity analysis also shows that the robustness of the solutions given by the solving method increases when the uncertainty grows. (shrink)

How do engineers respond to ethical dilemmas that occur in practice? How do they view their individual and collective responsibilities? How do they make decisions before all the facts are in? Using the space shuttle programme as the framework, this book examines the role of ethical decision making in the practice of engineering. In particular, the book considers the design and development of the main engines of the space shuttle as a paradigm for how individual engineers perceive, articulate, and resolve (...) ethical dilemmas in a large, complex organisation. A series of in-depth case studies show engineers at work on various stages of the project as they balance budgets, deadlines and risks. By documenting the historical development of a single system, the book provides a unique opportunity to explore the complex interactions between political, organisational and technical pressures and engineering and management decisions. (shrink)

As one of the most effective medical technologies for the infertile patients, in vitro fertilization has been more and more widely developed in recent years. However, prolonged waiting for IVF procedures has become a problem of great concern, since this technology is only mastered by the large general hospitals. To deal with the insufficiency of IVF service capacity, this paper studies an IVF queuing network in an integrated cloud healthcare system, where the two key medical services, that is, egg retrieval (...) and transplantation, are assigned to accomplish in the general hospital, while the routine medical tests are assigned into the community hospital. Based on continuous-time Markov procedure, a dynamic large-scale server scheduling problem in this complicated service network is modeled with consideration of different arrival rates of multiple type of patients and different service capacities of multiple servers that can be defined as doctors of the general hospital. To solve this model, a reinforcement learning algorithm is proposed, where the reward functions are designed for four conflicting subcosts: setup cost, patient waiting cost, penalty cost for unsatisfied patient personal preferences, and medical cost of patient. The experimental results show that the optimal service rule of each server’s queue obtained by the RL method is significantly superior to the traditional service rule. (shrink)

Compared to a charging scheduling and management problem characterized by predetermined trip assignment, this study takes bus and driver scheduling into account, and mealtime windows must be guaranteed as one of the major labor regulations. A discretized mixed-integer linear programming model is developed based on a single electric bus route. We aim to obtain fast and high-quality global solutions for this problem, and the model can be easily executed by bus operators by directly invoking an available optimization solver (...) such as IBM ILOG CPLEX. We test our model on a real round-trip bus route. Numerical experiments show that CPLEX takes approximately 6 sec to obtain an optimal solution. The model can not only reasonably arrange daily trips for each electric bus and driver but also effectively determine the optimal charging schedule and management for an electric bus line. Besides, we analyze the sensitivity of the key parameters in the model. With the increase in the drivers’ maximum workload, the drivers’ average idle time decreases by approximately 11.25%. The objective value decreases by approximately 38.71% and 40.04% with increases in the battery capacity and fleet size, respectively, and the objective value increases by approximately 30.06% with the decrease in the initial battery driving range. In addition, we compare the effectiveness of our time discretization modeling method in solving the same case study to that from other similar studies, and the validity of our method can be verified by the calculation time. We also compare the computational efficiency of CPLEX in solving the same case study problem with and without implementing valid inequalities, and the computational efficiency of the valid inequality method is greatly improved. Finally, through the testing of a multiline network, the potential application of the model to a large-scale traffic network is verified. (shrink)