A decision support approach to automatic timetabling in higher education institutions

Fernandes, Pedro; Pereira, Carla; Barbosa, Armando

doi:10.1007/s10951-015-0435-z

Cited by 3 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies on this problem have been based on unrealistic models with limited practical application. This paper [32] summarizes the work by Bullet Solutions, which focused on understanding and modeling the problem, developing robust algorithms, and employing optimization methods. The BTTE application, resulting from this work, achieved high-quality results with signi cant time savings (85%) in all analyzed cases.…”

Section: Decision Support Systemsmentioning

confidence: 99%

Integrating Semantic Web Technologies in Higher Education: A Decision Support System for University Selection

Shah,

Khiyal,

Awan

2024

Preprint

View full text Add to dashboard Cite

The process of choosing an appropriate university is a significant and complex decision for both students and academics. The challenge lies in efficiently navigating and interpreting the vast amount of unstructured and semi-structured data available online. To tackle this issue, this paper introduces a sophisticated decision support system designed to aggregate and integrate data from diverse sources, such as university websites and other online platforms. This system employs semantic web technologies and various datasets for automatic information extraction, facilitating a more streamlined data analysis process. Key attributes such as research output, student demographics, geographical location, and overall rankings are utilized as parameters for data integration. The system is equipped with a user-friendly interface that offers customizable visualization tools. These tools enable users to prioritize and compare universities based on their individual preferences effectively. For empirical validation, we gathered and analyzed data from 301 universities in the United Kingdom, employing both manual and automated techniques for information extraction. The outcomes of this study underscore the efficiency and practicality of our approach in simplifying the university selection process for potential students and faculty members. Overall, this system presents itself as an invaluable resource for informed decision-making in the domain of higher education.

show abstract

Section: Decision Support Systemsmentioning

confidence: 99%

Integrating Semantic Web Technologies in Higher Education: A Decision Support System for University Selection

Shah,

Khiyal,

Awan

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…SOA (Service-Oriented Architecture) is a service-oriented architecture [25]. It refers to diferent functional units of an application as services, which are connected by well-defned interfaces and contracts between these services [26]. For SOA-based information integration, frst and foremost, enterprise business function module rationalisation and modularization, as well as information access, should be carried out to achieve reusability of business function modules, which is the foundation for generating new services and processes through service composition arrangements [27].…”

Section: Soa-based Enterprise-wide Information Integration Platformmentioning

confidence: 99%

SOA-based Information Integration Platform for Educational Management Decision Support System

Wang

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The resource management platform based on the resource library has different structures, which brings a lot of inconvenience to the sharing of educational resources. However, the scale of the school is constantly expanding, the number of campuses and departments within the school increases, and the number of teachers and students increases. These new circumstances need the development of an open, secure, and effective school administration system that can operate online at any time and from any location. The “plan norm model” of educational management decision-making goals controls the decision-making dynamic structure. Whether the decision-making object is an “economic man” or a “social man,” its dynamic structure is built on a top-down control sequence, with the only variation being the control mechanisms used. In colleges and universities, educational administration management is an essential aspect of educational management. It is a work with strong timeliness, heavy workload, and high accuracy requirements, affecting the overall situation of teaching. This paper proposes an information integration platform based on SOA, which integrates various enterprise application systems into a unified platform by using a loose coupling structure, realizes information sharing among application systems, and meets the needs of cross-departmental enterprise business. As a new architecture idea, service-oriented architecture can package existing assets and reuse existing assets. It can also minimize the impact of demand changes because its implementation is loosely coupled. When users need to add or modify a function, they only need to make a few modifications in the presentation layer or business process layer.

show abstract

“…In changing environments, the uncertainty factor in decision making in NSP is a serious issue. Indeed, researches on intelligent decision support system have been carried out [26][27][28]. Dynamic scheduling have been applied in [29][30][31].…”

Section: Dynamic Schedulingmentioning

confidence: 99%

“…In changing environments, the uncertainty factor in decision making in NSP is a serious issue. Indeed, researches on intelligent decision support system have been carried out [26][27][28]. In home healthcare scenario, time required for the assignment of a nurse must be made in time as per the request generated by a patient.…”

Section: Dynamic Schedulingmentioning

confidence: 99%

A Patient-Centric Nurse Scheduling Algorithm

2021

View full text Add to dashboard Cite

This paper introduces a new approach to the well-studied nurse scheduling problem. Nurse scheduling problem involves multiple inter-related parameters concerning nurse and patients, which makes the problem too complex. As a result, many of the traditional NSPs are forced to consider only the nurse-respective parameters for generating the schedules. In this paper, we have considered patient recovery as the ultimate objective of nurse scheduling. To achieve this, we have considered patient's needs and priorities besides the nurse skills, and environment (e.g. logistic) parameters as basic constraints. This paper aims to minimize soft constraints as well as to improve patient's satisfaction and quality of service of nurse assignment. We have defined a number of hard and soft constraints based on patient's requirements, ailments, preferences for a particular nurse, nurse's skill parameters, penalty, demands on duties, matching quotient with patient's requirements, location, etc. The assignment of nurses to patients for a particular shift depend on the relation between patient's need and the skill factor of the nurse, besides, of course, the availability factor of the nurse. This helps in achieving efficiency of the overall solution, besides properly supporting qualitative issues. In this regards, two objective functions are devised here to maximize the nurse's rewards and minimize the scheduling computational cost. The resulting algorithm has been tested on real-case scenarios of a nursing centre, providing evidence of the actual advantages of the proposed solution.

show abstract

A decision support approach to automatic timetabling in higher education institutions

Cited by 3 publications

References 14 publications

Integrating Semantic Web Technologies in Higher Education: A Decision Support System for University Selection

Integrating Semantic Web Technologies in Higher Education: A Decision Support System for University Selection

SOA-based Information Integration Platform for Educational Management Decision Support System

A Patient-Centric Nurse Scheduling Algorithm

Contact Info

Product

Resources

About