Local search for the surgery admission planning problem

We present a model for the surgery admission planning problem, and a meta-heuristic algorithm for solving it. The problem involves assigning operating rooms and dates to a set of elective surgeries, as well as scheduling the surgeries of each day and room. Simultaneously, a schedule is created for each surgeon to avoid double bookings. The presented algorithm uses simple Relocate and Two-Exchange neighbourhoods, governed by an iterated local search framework. The problem's search space associated with these move operators is analysed for three typical fitness surfaces, representing different compromises between patient waiting time, surgeon overtime, and waiting time for children in the morning on the day of surgery. The analysis shows that for the same problem instances, the different objectives give fitness surfaces with quite different characteristics. We present computational results for a set of benchmarks that are based on the admission planning problem in a chosen Norwegian hospital

Solar radiation on Adana, Turkey

Measured monthly mean daily global radiation data for Adana (Lat. 37° 00' N, Long. 35° 20' E) has been used for estimating global horizontal solar-radiation. Hourly global, diffuse and direct solar-radiations on a horizontal surface in Adana have been determined. © 2002 Elsevier Science Ltd. All rights reserved

Solar radiation on Adana, Turkey

Measured monthly mean daily global radiation data for Adana (Lat. 37° 00' N, Long. 35° 20' E) has been used for estimating global horizontal solar-radiation. Hourly global, diffuse and direct solar-radiations on a horizontal surface in Adana have been determined.Solar radiation Diffuse and direct radiation Clearness index Horizontal surface Adana

ENERGY CONSUMPTION MANAGEMENT IN TEXTILE FINISHING PLANTS: A COST EFFECTIVE AND SEQUENCE DEPENDENT SCHEDULING MODEL

Bu çalışmada tekstil terbiye işletmelerinde, etkin bir çizelgeleme yaklaşımıyla, enerji tüketimi yönetiminin sağlanması ve enerji maliyetlerinin azaltılması amaçlanmaktadır. Bu çizelgeleme yaklaşımında, sıralamaya bağlı hazırlık işlemleri süreleri, sıralamaya bağlı hazırlık işlemleri enerji tüketimleri ve zamana bağlı elektrik enerjisi tarifesi bir bütün halinde ele alınmaktadır. Tekstil terbiye işletmeleri, esnek atölye tipi üretim ortamlarının tipik örnekleridir. Bu yüzden, yapılan çalışmada sıralamaya bağlı esnek atölye tipi üretim ortamları için yeni bir enerji tasarruflu, karma tam sayılı doğrusal programlama modeli önerilmektedir. Önerilen model aktüel çizelgeleme problemlerini karşılayabilen dört bileşenli bir maliyet fonksiyonunu içermekte olup, modelin yeterliliği gerçek zamanlı üretim verileriyle sınanmıştır.ABSTRACT This study focuses on managing energy consumption and reducing energy costs in textile finishing plants with an effective scheduling approach, which consists of sequence dependent set-up times, sequence dependent set-up energy usages and time-of-use energy tariff. The finishing plants are typical examples of the flexible job shops. Therefore, a novel energy saving mixed-integer linear programming model is proposed for the sequence dependent flexible job shop scheduling problems in this study. The proposed model comprises an extended cost function that has a quaternary structure for tackling actual scheduling problems. The capability of the developed model is evaluated with actual manufacturing data

ENERGY CONSUMPTION MANAGEMENT IN TEXTILE FINISHING PLANTS: A COST EFFECTIVE AND SEQUENCE DEPENDENT SCHEDULING MODEL

Bu çalışmada tekstil terbiye işletmelerinde, etkin bir çizelgeleme yaklaşımıyla, enerji tüketimi yönetiminin sağlanması ve enerji maliyetlerinin azaltılması amaçlanmaktadır. Bu çizelgeleme yaklaşımında, sıralamaya bağlı hazırlık işlemleri süreleri, sıralamaya bağlı hazırlık işlemleri enerji tüketimleri ve zamana bağlı elektrik enerjisi tarifesi bir bütün halinde ele alınmaktadır. Tekstil terbiye işletmeleri, esnek atölye tipi üretim ortamlarının tipik örnekleridir. Bu yüzden, yapılan çalışmada sıralamaya bağlı esnek atölye tipi üretim ortamları için yeni bir enerji tasarruflu, karma tam sayılı doğrusal programlama modeli önerilmektedir. Önerilen model aktüel çizelgeleme problemlerini karşılayabilen dört bileşenli bir maliyet fonksiyonunu içermekte olup, modelin yeterliliği gerçek zamanlı üretim verileriyle sınanmıştır.ABSTRACT This study focuses on managing energy consumption and reducing energy costs in textile finishing plants with an effective scheduling approach, which consists of sequence dependent set-up times, sequence dependent set-up energy usages and time-of-use energy tariff. The finishing plants are typical examples of the flexible job shops. Therefore, a novel energy saving mixed-integer linear programming model is proposed for the sequence dependent flexible job shop scheduling problems in this study. The proposed model comprises an extended cost function that has a quaternary structure for tackling actual scheduling problems. The capability of the developed model is evaluated with actual manufacturing data

Can neural network able to estimate the prognosis of epilepsy patients accorrding to risk factors?

PubMedID: 20703908The aim of this study is to evaluate the underlying etiologic factors of epilepsy patients and to predict the prognosis of these patients by using a Multi-Layer Perceptron Neural Network (MLPNN) according to risk factors. 758 patients with epilepsy diagnosis are included in this study. The MLPNNs were trained by the parameters of demographic properties of the patients and risk factors of the disease. The results show that the most crucial risk factor of the epilepsy patients was constituted by the febrile convulsion (21.9%), the kinship of parents (22.3%), the history of epileptic relatives (21.6%) and the history of head injury (18.6%). We had 91.1 % correct prediction rate for detection of the prognosis by using the MLPNN algorithm. The results indicate that the correct prediction rate of prognosis of the MLPNN model for epilepsy diseases is found satisfactory. © 2009 Springer Science+Business Media, LLC

Scheduling operating rooms: achievements, challenges and pitfalls

In hospitals, the operating room (OR) is a particularly expensive facility and thus efficient scheduling is imperative. This can be greatly supported by using advanced methods that are discussed in the academic literature. In order to help researchers and practitioners to select new relevant articles, we classify the recent OR planning and scheduling literature into tables regarding patient type, used performance measures, decisions made, OR up- and downstream facilities, uncertainty, research methodology and testing phase. Based on these classifications, we identify trends and promising topics. Additionally, we recognize three common pitfalls that hamper the adoption of research results by stakeholders: the lack of a clear choice of authors on whether to target researchers (contributing advanced methods) or practitioners (providing managerial insights), the use of ill-fitted performance measures in models and the failure to understandably report on the hospital setting and method-related assumptions. We provide specific guidelines that help to avoid these pitfalls. First, we show how to build up an article based on the choice of the target group (i.e., researchers or practitioners). Making a clear distinction between target groups impacts the problem setting, the research task, the reported findings, and the conclusions. Second, we discuss points that need to be considered by researchers when deciding on the used performance measures. Third, we list the assumptions that need to be included in articles in order to enable readers to decide whether the presented research is relevant to them