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In this note, a new solution procedure similar to critical path analysis in network theory is developed for determining dynamic uncapacitated lot sizing in multi-stage production systems. The algorithm offered is a Decision Network Algorithm. An example is given to illustrate the algorithm. Keywords: Dynamic lot-size; Decision network; Multi-stage

A branch and bound algorithm was formulated to resolve the one-machine scheduling problem. The algorithm specifically intends to lessen the maximum earliness with least number of tardy jobs. Implementation of the algorithm revealed its effectiveness for the problems of up to 25 jobs. Results showed that as the tardiness factor decreases and the problem size increases, the algorithm's computing time rises.

The performance of a multi-item, multi-line, multi-stage just in time (JIT) system tends to be affected by the number of Kanbans used. Utilization of a simulation analysis showed that a rise in the number of Kanbans creates a corresponding rise in the system's output rate and utilization. A significant rise in waiting times and work-in-process (WIP) lengths was also observed as the number of Kanbans increases.

This article focuses on determining the best routes between affected areas and relief depots in sudden-onset disasters and selecting the best depot that can serve at the shortest response time. These decisions are crucial in emergency humanitarian logistics management since the response time to affected areas dramatically influences the survival rate and timely availability of relief items. This article considers many real-life aspects to deal with the problem realistically. A framework based on Geographic Information System (GIS) is presented that takes into account widths and structures of different types of infrastructure (roads, tunnels, and bridges), the survivability of infrastructure according to its spatial proximity to a potential disaster, and legal speed limits in the pre- and post-disaster decision processes. A case study was carried out for an earthquake disaster scenario in Erzincan province of Turkey and various scenarios were generated to analyze the solutions under different conditions.

This multi-centre study aimed to determine the antibiotic consumption in Turkish hospitals by point prevalence. Antibiotic consumption of 14 centres was determined using the DDD method. Among hospitalized patients, 44.8% were using antibiotics and the total antibiotic consumption was 674.5 DDD/1000 patient-days (DPD). 189.6 (28%) DPD of the antibiotic consumption was restricted while 484.9 (72%) DPD was unrestricted. Carbapenems (24%) and beta lactam/beta lactamase inhibitors (ampicillin-sulbactam or amoxicillin-clavulanate; 22%) were the most commonly used restricted and unrestricted antibiotics. Antibiotics were most commonly used in intensive care units (1307.7 DPD). Almost half of the hospitalized patients in our hospitals were using at least one antibiotic. Moreover, among these antibiotics, the most commonly used ones were carbapenems, quinolones and cephalosporins, which are known to cause collateral damage. We think that antibiotic resistance, which is seen at considerably high rates in our hospitals, is associated with this level of consumption.

Scheduling is the allocation of resources over time to perform a collection of task. It is an important subject of production and operations management area. For most of scheduling problems made so far, the processing times of each job on each machine and due dates have been assigned as a real number. However in the real world, information is often ambiguous or imprecise. In this paper fuzzy concept are applied to the flow shop scheduling problems. The branch-and-bound algorithm of Ignall and Schrage was modified and rewritten for three-machine flow shop problems with fuzzy processing time. Fuzzy arithmetic on fuzzy numbers is used to determine the minimum completion time (Cmax). Proposed algorithm gets a scheduling result with a membership function for the final completion time. With this membership function determined, a wider point of view is provided for the manager about the optimal schedule.

AbstractObjective:To assess the quality of antibiotic prophylaxis for clean and clean-contaminated elective surgical procedures.Design:A cross-sectional, country-wide survey.Setting:Thirty-six hospitals in 12 cities in Turkey.Participants:Four hundred thirty-nine surgeons from 6 different specialties who performed selected procedures of interest.Methods:A random sample of surgeons from different hospitals was selected. A standardized data collection form was used to record the type of procedure, the names, doses, timing of the first doses, and duration of antibiotics, important decisive factors, and problems in the management of prophylactic antibiotic use for surgical procedures.Results:Fifty-five percent of surgeons addressed completed the survey. For clean-contaminated procedures, 6% of surgeons did not use antibiotic prophylaxis, whereas 88% used more than a single dose. Inappropriate antibiotics were chosen for 32% of procedures. In 39% of procedures, the first dose of antibiotics was not administered during induction of anesthesia. Duration of prophylaxis was longer than 24 hours in 80% and longer than 48 hours in 46% of all procedures. Only 112 surgeons (26%) were using definitely appropriate prophylaxis in all ways. Multivariate analysis revealed that surgeons in university hospitals (OR, 2.353; CI95, 1.426–3.884; P= .001) and general surgeons (OR, 4.986; CI95, 2.890–8.604; P< .001) used antibiotic prophylaxis more appropriately. Patients not covered by health insurance (OR, 0.417; CI95, 0.225–0.772; P< .001) were associated with inappropriate prophylaxis.Conclusion:Given the high frequency of antibiotics prescribed for surgical prophylaxis in Turkey, adherence to surgical prophylaxis guidelines is urgently needed.

Hazardous waste management involves the collection, transportation, processing, recycling and disposal of industrial and domestic wastes. In this study, a single objective, multi-product mixed integer programming model for hazardous waste facility location and routing problem is developed for the hazardous waste management problem. The aim of the study is to locate hazardous waste treatment, recycling and disposal facilities to the designated candidate locations with the lowest cost and highest profit. With this, we try to ensure that the waste is transported between hazardous waste generation centers and these facilities with the minimum cost and maximum revenue. Unlike the studies in the literature, we constructed an enhanced model that take all the following properties into account: the location of hazardous waste treatment, recycling and disposal facilities; transportation of hazardous waste, hazardous recycled materials and hazardous waste residues between these facilities; cost, revenue, risk, capacity and technology compatibility. The model provides to decide the sorts of facilities which are needed by considering the type and amount of hazardous waste generated in determining where to locate these facilities. The model, also, determines which types of hazardous waste can be transported between the facilities. The developed model is applied to the Marmara Region with the real data provided by the Republic of Turkey Ministry of Environment and Urbanization. Accordingly, the results are evaluated and presented.