Optimal Schedule of Home Care Visits for a Health Care Center

Alves, Filipe; Pereira, Ana I.; Fernandes, Florbela P.; Fernandes, Adília; Leitão, Paulo; Martins, Anabela Correia

doi:10.1007/978-3-319-62398-6_10

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…Some approaches and applications in the HHC domain, have already been developed, involving a health unit, in a real implementation environment with a specific real dataset (Alves et al, 2019a;Alves et al, 2019b;and Alves et al, 2017). However, in recent times, studies point to the need to introduce intelligent systems with fast reaction in dynamic environments, mainly due to the lack of flexibility of the most classical optimization techniques.…”

Section: Home Health Carementioning

confidence: 99%

Conceptual Multi-Agent System Design for Distributed Scheduling Systems

Alves¹,

Rocha²,

Pereira³

et al. 2022

Smart and Sustainable Manufacturing Systems for Industry 4.0

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With the progressive increase in the complexity of dynamic environments, systems require an evolutionary configuration and optimization to meet the increased demand. In this sense, any change in the conditions of systems or products may require distributed scheduling and resource allocation of more elementary services. Centralized approaches might fall into bottleneck issues, becoming complex to adapt, especially in case of unexpected events. Thus, Multi-agent systems (MAS) can extract their automatic and autonomous behaviour to enhance the task effort distribution and support the scheduling decision-making. On the other hand, MAS is able to obtain quick solutions, through cooperation and smart control by agents, empowered by their coordination and interoperability. By leveraging an architecture that benefits of a collaboration with distributed artificial intelligence, it is proposed an approach based on a conceptual MAS design that allows distributed and intelligent management to promote technological innovation in basic concepts of society for more sustainable in everyday applications for domains with emerging needs, such as, manufacturing and healthcare scheduling systems.

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Section: Home Health Carementioning

confidence: 99%

Conceptual Multi-Agent System Design for Distributed Scheduling Systems

Alves¹,

Rocha²,

Pereira³

et al. 2022

Smart and Sustainable Manufacturing Systems for Industry 4.0

View full text Add to dashboard Cite

show abstract

“…This optimization problem are complex, where specific requirements have to be considered, such as matching nurses' skill and patients, regulations or workload balance measurements. Exact methods, hybrid methods or metaheuristics provided optimal solutions, mainly in the HHC operations planning or routes timing [7,2]. Most works are limited to daily operations and consider only static and deterministic contexts.…”

Section: Relationship To Applied Artificial Intelligence Systemsmentioning

confidence: 99%

“…Some simulations already carried out, in real context, using deterministic and/or stochastic methods, have benefited in obtaining optimized solutions and significantly improving the profitability of planning. Some results of resource allocation and scheduling in a health unit managed to reduce (approximately 30%) the maximum time spent in route to existing plans [2].…”

Section: Contribution and Innovationmentioning

confidence: 99%

Multi-agent System Architecture for Distributed Home Health Care Information Systems

Alves

Rocha

Pereira

et al. 2021

IFIP Advances in Information and Communication Technology

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In recent years, the aging population has increased. The intervention of home health care (HHC) has been an asset, however, needs technological innovation for the high level of complexity and requirements. Innovation in the HHC system is crucial, since management still occurs manually using classical methods, usually centralized and static. The mapping of real HHC problems, enables an application model of a distributed intelligent system, considering the operational planning needs, promoting an ecosystem of digital and sustainable technologies. This work aims to specify a versatile and flexible architecture for allocation, routing, and scheduling tasks in distributed HHC. It considers multi-agent systems technology to guarantee the fast response to condition changes in existing planning, merged with optimization algorithms that allow achieving optimal solutions. Collaboratively, the information digitization for real-time monitoring will coordinate a socialized solution using different tools and techniques, ensuring robustness and dynamic responsiveness in a domain with emerging needs.

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“…The steps of PSO are summarized in the following algorithm ( Figure 6). During the iterative process if x i k+1 is not a feasible solution, the coordinate that is not feasible will be projected to the feasible region [26]. The iterative procedure terminates after a maximum number of iterations or after a maximum number of function evaluations.…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

A human centered hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment

Alves¹,

Leonilde²,

Rocha³

et al. 2019

FME Transactions

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Manufacturing activities and production control are constantly growing. Despite this, it is necessary to improve the increasing variety of scheduling and layout adjustments for dynamic and flexible responses in volatile environments with disruptions or failures. Faced with the lack of realistic and practical manufacturing scenarios, this approach allows simulating and solving the problem of job shop scheduling on a production system by taking advantage of genetic algorithm and particle swarm optimization algorithm combined with the flexibility and robustness of a multi-agent system and dynamic rescheduling alternatives. Therefore, this hybrid decision support system intends to obtain optimized solutions and enable humans to interact with the system to properly adjust priorities or refine setups or solutions, in an interactive and user-friendly way. The system allows to evaluate the optimization performance of each one of the algorithms proposed, as well as to obtain decentralization in responsiveness and dynamic decisions for rescheduling due to the occurance of unexpected events.

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Optimal Schedule of Home Care Visits for a Health Care Center

Cited by 5 publications

References 9 publications

Conceptual Multi-Agent System Design for Distributed Scheduling Systems

Conceptual Multi-Agent System Design for Distributed Scheduling Systems

Multi-agent System Architecture for Distributed Home Health Care Information Systems

A human centered hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment

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