Przemyslaw Korytkowski

Predictors of long-term smoking cessation: results from the global adult tobacco survey in Poland (2009–2010)

BackgroundExpanding the information on determinants of smoking cessation is crucial for developing and implementing more effective tobacco control measures at the national as well as European levels. Data on smoking cessation and its social correlates among adults from middle-income countries of Central and Eastern Europe are still poorly reported in the literature. The aim of the study was to analyze the association of socio-demographic indicators with long term tobacco smoking cessation (quit smoking for at least one year prior to interview) among adults. Moreover, we evaluated motives for giving up smoking from former smokers.MethodsData on former as well as current smokers’ socio-demographic and smoking-related characteristics were derived from the Global Adult Tobacco Survey (GATS). GATS is a cross-sectional, nationally representative household survey implemented in Poland between 2009 and 2010. GATS collected data on a representative sample of 7,840 individuals including 1,206 individuals who met the criteria of long-term smoking cessation and 2,233 current smokers. Smoking cessation rate was calculated as the number of former smokers divided by the number of ever smokers. Logistic regression analyses were used to obtain odds ratios (ORs) and 95% confidence interval (CI) of the broad number of variables on successful cessation of smoking.ResultsAmong females the quit rate was 30.4% compared to 37.9% in males (p < 0.01). Former smokers declared concerns about the health hazard of smoking (60.8%) and the high price of cigarettes (11.6%) as primary reasons for smoking cessation. Older age, high education attainment, awareness of smoking health consequences was associated with long-term quitting among both genders. Also employed males had over twice the probability of giving up smoking compared with unemployed, and being religious did not contribute to successful smoking cessation.ConclusionResults indicated that smoking cessation policies focused on younger age groups are vital for curbing tobacco epidemic in Poland and should become a public health main concern. There is also the need for interventions to raise awareness on smoking health risks and quitting benefits are crucial to increase cessation potential among adult smokers. Nevertheless further effort needs to be done to prevent smoking uptake.

An evolutionary simulation-based optimization approach for dispatching scheduling

Abstract An effective scheduling decision is one of the key factors towards improving the efficiency of a system’s performance, particularly in the instance of multiple products thus dispatching rules have been widely used for real-time scheduling because they can provide a very quick and pretty good solution. However, deciding how to select appropriate rules is very difficult. In this paper, we develop evolutionary simulation-based heuristics to construct near-optimal solutions for dispatching rule allocation. Our heuristic is easy to use and gives a manager a useful tool for testing a configuration that can minimize certain performance measures. The optimization heuristics are used to determine priority strategies to maximize the performance of a complex manufacturing system with a large number of different products, along with an overtime that changes with a mix of different process types, including assembly and disassembly operations and with different types of internal and external disturbances. Modeling is carried out using discrete-event simulation. Case study analysis is of a commercial offset printing production system.

Competence-based performance model of multi-skilled workers

Performance model of multi-skilled workers with learning curves and competence sets.Novel calculation of worker performance.Combination of the competences-based performance with a discrete-event simulation. Effective human resource management requires an individual approach to worker appraisal in order to be able to make accurate analyses and to make informed decisions. In this paper we develop a competences-based analytical model of the performance of multi-skilled workers undertaking repetitive tasks. The aim is to build an analytical tool that better describes the capabilities of workers to perform repetitive tasks by binding together hierarchical competences modeled as a weighted digraph and learning curves to express individual learning rates. An illustrative example based on an assembly line using a discrete-event simulation model is provided. As a result we get an approach that calculates how work experience on one working post translates into performance on other posts, thus enabling better workforce scheduling. Incorporating competences-based modeling into planning and scheduling results in a more precise estimation of actual and future workforce performance.

Toward an excellence-based research funding system: Evidence from Poland

This article discusses the metrics used in the national research evaluation in Poland of the period 2009–2012. The Polish system uses mostly parametric assessments to make the evaluation more objective and independent from its peers. We have analysed data on one million research outcomes and assessment results of 962 scientific units in the period 2009–2012. Our study aims to determine how much data the research funding system needs to proceed with evaluation. We have used correlation analysis, multivariate logistic regressions models and decision trees to show which metrics of the evaluation played a major role in the final results. Our analysis revealed that many metrics taken into account in the evaluation are closely correlated. We have found that in the Polish system, not all the collected data are necessary to achieve the main goal of the system, namely the categorization of scientific units in terms of their research performance. Our findings highlight the fact that there is a high correlation between performance in terms of publications and the scientific potential of a given scientific unit. We conclude with recommendations and a suggestion of a transition from a system in which the scientific units report all their metrics to a system in which they show only the most important metrics that meet the requirements of excellence in research.

Competences-based performance model of multi-skilled workers with learning and forgetting

A performance model of multi-skilled workers with learn and forget curve is proposed.The algorithm relies on a model of required and possessed competences.The algorithm is provided for estimation of production output or production time. The relationship between performance and experience is non-linear, thus planning models that seek to manage workforce development through task assignment are difficult to solve. This gets even more complicated when taking into account multi-skilled workers that are capable of performing a variety of tasks. In this paper we develop a competences-based analytical model of the performance of multi-skilled workers undertaking repetitive tasks, taking into account learning and forgetting. A learning curve can be used to estimate improvement when repeating the same operation. Inverse phenomenon is forgetting, which can occur due to interruption in the production process. The Performance Evaluation Algorithm (PEA) was developed for two cases: fixed shift duration and fixed production output. The aim was to build a tool that better describes the capabilities of workers to perform repetitive tasks by binding together hierarchical competences modeled as a weighted digraph together with a learning and forgetting curve model (LFCM) to express individual learning rates.

Modeling and Performance Optimization of a Distributed Production System

Abstract An approach, based on queuing modeling and simulation, to resource allocation for a distributed production system is examined in the paper. The problem is formulated as an objective function minimization for a queuing network. The optimization is based on the combination of analytical modeling and simulation. The analytical model is used for primary evaluation and branching for the optimization algorithm. The simulation is used for validation of analytical results and algorithm stop decision. Copyright© 2001 IFAC

Simulation-based optimisation of inspection stations allocation in multi-product manufacturing systems

In this paper a multi-product production systems (MPPS) with in-line quality control is examined. The problem of determining the optimal inspection strategy that results in lowest total inspection cost, while assuring required outgoing quality level is modelled discrete-event simulation is used to model the production system. The optimal allocation is determined by using a tabu search algorithm.

A genetic algorithm with tournament selection for optimising inspection allocation in multiproduct multistage production systems

Multiproduct multistage production systems have been widely implemented in recent years. One of the important considerations in such systems is identifying the location of inspection stations. This paper considers a multiproduct setting where part types compete with each other for common production resources. In this environment, it is important to consider factors such as throughput time variability and to include the corresponding queuing aspects into the model. Each workstation is modelled as a GI/G/c queue. The optimal allocation is determined by using a genetic algorithm with tournament selection, one-point crossover and uniform mutation.

Creating learning objects and learning sequence on the basis of semantic networks

With the growing popularity of distance courses the demand for good didactic materials also increases. However, preparing such material is a complicated task, often done in an inproper way, by simply transforming traditional teaching/learning material into a digital form. In such case, one of the most important aspects of learning - the presence of a teacher, is not considered. The following paper presents a method that allows creating didactic materials for distance learning that could compensate for the lack of direct contact with a teacher in the learning process.

OPTIMIZATION OF PRODUCTION CAPACITY IN INTANGIBLE FLOW PRODUCTION SYSTEMS

Abstract The goal of the paper is to present a model and algorithms for optimizing the production capacity of an intangible flow production system with the given network structure. The production capacity optimization problem is presented as a task of ***multi-criterion optimization with discrete, non-linear goal functions. The proposed solution enables finding an optimal configuration of the flow production system which is interpreted as a queuing network.