MODELOS Y MÉTODOS DE OPTIMIZACIÓN LINEAL CON INCERTIDUMBRE: UNA BREVE REVISIÓN DEL ESTADO DEL ARTE

In the modeling of many problems on linear optimization is not possible to consider the classic deterministic model because the set of parameters is not fully known due to the significant variation of the data along time or because there is no uniformity on the values. These kind of problems are known as problems with uncertainty and there are different approaches about modeling and methods of solution to resolve them. In this paper we make a review of such approaches focusing basically in stochastic optimization, fuzzy optimization, intervaling optimization and hybrid optimization. The difference between these approaches is perceived in the nature of the data, notions of feasibility and optimality and computational requirements, among others.En la modelación de muchos problemas de optimización lineal no es posible considerar el modelo clásico determinista, porque el conjunto de los parámetros no son completamente conocidos debido a que los datos varian en forma significativa a lo largo del tiempo o porque no hay homogeneidad en los valores.Estos problemas son conocidos como problemas con incertidumbre, para los cuales existen diversos enfoques en la modelación y en los métodos de solución. En este artículo se revisa tales enfoques, incidiendo fundamentalmente en la optimización estocástica, optimización difusa, optimización intervalar y optimización híbrida. La diferencia entre estos enfoques se perciben en la naturaleza de los datos, nociones de factibilidad y optimalidad, requerimientos computacionales, entre otros

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

A layout design decision-support framework and concept demonstrator for rural hospitals using mixed methods

Thesis (MEng)--Stellenbosch University, 2017.ENGLISH ABSTRACT: Layout design is an ever-present problem that has a significant effect on the operations of an organisation, especially in the context of healthcare which deals with the lives of patients. It is a complex problem that has long-term consequences and oftentimes competing objectives. Literature has focused almost exclusively on using either quantitative or qualitative layout design methods for designing layouts. This study develops a generic framework using both quantitative and qualitative layout design methods that will guide the user to design a near optimal layout for a rural hospital while taking into consideration the relevant laws and standards as well as the health outcomes of the surrounding rural community. Rural and urban lifestyles, health, and illnesses differ in many ways. General hospital design methods are therefore not necessarily appropriate for hospitals in these areas. There is thus a need for a framework to be tailored for a rural community. Following a mixed methods methodology, a systematic literature review of quantitative and qualitative layout design methods along with hospital design considerations were conducted in order to determine the most adequate methods for designing a hospital layout at the block diagram level of detail. Furthermore, the commonalities and differences between rural and urban hospitals were investigated including laws and standards relevant to hospital layouts. The qualitative layout design methods involved different layout procedures and Muther’s Systematic Layout Planning Procedure was found to be most adequate. Furthermore, hospital design considerations such as patient-centeredness, efficiency, flexibility and expandability, sustainability, and therapeutic environment were identified and linked with the quantitative layout methods. It was also found that rural communities have different needs to urban ones with regard to access to medical care, prominent illnesses, and attitudes towards health. The healthcare personnel shortages are particularly problematic for rural communities. The quantitative layout design methods involved layout models, solution methods (exact methods, metaheuristics, and hybrid metaheuristics), and layout software. Using criteria of objectives, assumptions, inputs, outputs, and hospital design considerations, the Quadratic Set Covering Problem was determined to be the most appropriate model for designing a rural hospital block diagram layout. It was deemed possible to integrate the quantitative and qualitative methods by embedding the qualitative data into this quantitative model. The rural hospital design framework was developed using Excel VBA and RStudio. The framework was validated via two routes. Firstly, semi-structured interviews were conducted with experts in the field, i.e. expert analyses. Secondly a case study of the Semonkong Hospital Project was employed wherein the framework was applied successfully. The framework was deemed valid according to both the expert analyses and the case study.AFRIKAANSE OPSOMMING: Die uitleg van ‘n gebou het ‘n belangrike impak op die bedrywighede van ‘n organisasie – veral in die konteks van gesondheidsorg waar daar met pasiënte se lewens gewerk word. Dit is ‘n ingewikkelde probleem wat oor langtermyneffekte beskik en dikwels teenstrydige doelwitte. Die literatuur vir uitleg ontwerpsmetodes het meestal gefokus op óf kwantitatiewe óf kwalitatiewe uitleg ontwerpsmetodes. Hierdie studie ontwikkel ‘n generiese raamwerk wat beide van hierdie metodes gebruik om ‘n gebruiker te lei om die uitleg van ‘n plattelandse hospital te ontwerp wat die gepaste wette en standaarde en die gesondheid van die omliggende gemeenskap in ag neem. Landelike- en stedelike gemeenskappe verskil in terme van hul lewenstyl, gesondheid en tipe siektes. Algemene uitleg ontwerpsmetodes is dus nie noodwendig geskik vir ‘n plattelandse hospitaal nie. Daar is dus ‘n behoefte om ‘n raamwerk te ontwikkel wat spesifiek is vir die uitleg van ‘n plattelandse hospitaal. Hierdie studie volg ‘n gemengde metode benadering en ‘n sistematiese literatuurstudie is gevolglik afsonderlik gedoen op kwantitatiewe- en kwalitatiewe uitleg ontwerpsmetodes met die doel om die mees geskikte ontwerpsmetodes vir ‘n hospitaal uitleg te bepaal. Die verskille en ooreenkomste tussen landelike- en stedelike hospitale was ook ondersoek. Hierdie sluit in wette en standaarde wat van toepassing is op hospitaal uitlegte. Die kwalitatiewe uitleg ontwerpsmetodes het verskillende uitleg prosedures ondersoek en dit is gevind dat Muther se Sistematiese Uitleg Prosedure die mees geskik is vir die probleem van hierdie studie. Daar is gevind dat die hoof ontwerpsoorwegings vir die uitleg van ‘n hospitaal pasiënt-gesentreerdheid, doeltreffendheid, aanpasbaarheid, volhoubaarheid en terapeutiese omgewing is. Daar is gevind dat landelike- en stedelike gemeenskappe verskil in terme van hul toegang tot mediese sorg, prominente siektes, en hul houdings teenoor gesondheid. Een van die grootste probleme in landelike hospitale was hul tekort aan personeel. Die kwantitatiewe uitleg ontwerpsmetodes sluit uitleg modelle, oplossingsmetodes (presiese metodes, metaheuristieke en hibriede metaheuristieke) en uitleg sagteware in. ‘n Kriteria van doelwitte, aannames, insette, uitsette en hospitaal ontwerpsoorwegings was gebruik om die mees geskikte uitleg model te kies naamlik: die ‘Quadratic Set Covering Problem’. Dit is gevind dat die kwantitatiewe- en kwalitatiewe uitleg ontwerpsmetodes deur middel van ‘embedding’ geïntegreer kan word. Die uitleg ontwerp raamwerk vir plattelandse hospitale was ontwikkel met behulp van Excel VBA en RStudio. Die raamwerk is bekragtig deur twee roetes. Eerstens, semi-gestruktureerde onderhoude was gevoer met kundiges in die velde van gesondheidsorg, plattelandse gemeenskappe en uitleg ontwerp. Tweedens, die raamwerk is toegepas op ‘n gevallestudie van die Semonkong Hospitaal Projek. Albei roetes dui daarop dat die raamwerk geldig is