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The purpose of this paper is to determine and evaluate resource allocation algorithms for mixed‐structure operation systems with unknown parameters characterized by experts using the formalism of C‐uncertain variables.

Aggregation and decomposition of mathematical models of operations, performed using analytical‐numerical optimization methods, lead to serial and parallel structures for which allocation algorithms are known. Evaluation of allocations carried out by means of a computer simulation.

Resource allocation problems for mixed‐structure operation systems may be solved by applying aggregation, decomposition and allocation algorithms determined for simple structures. Allocation algorithms based on C‐uncertain variables outperform these based on basic uncertain variables.

Application of the presented algorithms is limited to some mixed structures, however, the methodology used appears general enough to allow developing algorithms for other mixed structures.

The algorithms developed may be embedded into a knowledge‐based system supporting management‐level decisions concerning optimal distribution of limited financial resources.

Originally determined rules for aggregation and decomposition, as well as resulting allocation algorithms. The presented methodology seems promising for developing a general resource allocation algorithm – valid for any mixed structure of an operation system.

The purpose of this paper is to present results concerning resource distribution problems for a class of production systems composed of production operations described by relations with uncertain parameters – for newly considered serial‐parallel and parallel‐serial structures.

The resource distribution problems are formulated. For the typical mathematical model of a single production operation, the resource distribution algorithms are derived analytically or, when that is impossible, numerical procedures for finding solutions to distribution problems are suggested.

The uncertain variables have been proved as a convenient tool for solving specific optimization problems in production management based on relational knowledge representation with unknown parameters.

The paper presents analytical resource distribution and numerical algorithms for determining the optimal resource distribution, which may be applied in knowledge‐based management‐level decision systems for serial‐parallel and parallel‐serial structures of production systems.

The purpose of this paper is to examine the problem of rate allocation (RA) in computer networks in cases when some parameters are unknown or their values are imprecise.

The application of uncertain variables for the RA problems in computer networks in the presence of uncertainty is proposed.

Decision‐making problem formulations for RA in computer networks with unknown parameters of the utility functions and bandwidths based on the network utility maximization concept are given. Solution algorithms for all these problems are proposed.

It is assumed that an expert can describe possible values of unknown network parameters in the form of a certainty distribution. Then, the formalism of uncertain variables is applied and the knowledge of an expert is modelled with certainty distributions.

The RA algorithms obtained can be useful for designing and planning computer networks.

The new approach to the RA problem in computer networks in the presence of uncertainty, in cases when the probabilistic approach cannot be applied, is proposed and discussed.

The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems.

A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities.

Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services.

This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode.

A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.

The study aims to examine the factors that determine the success of graduates in the labour market. This success is measured in several ways, namely, above-average wages in the economy, employment in accordance with the field of study and job satisfaction. The research explores the employment outcomes of graduates from Jagiellonian University, which is the oldest and one of the best in Poland. Not only does the analysis focus on degree-related predictors such as discipline or faculty, but it is also extended to include activities undertaken during studies and family background.

The analysis is based on data collected in the graduates' career survey, which is conducted six months after graduation. For this article, a database of over 6,000 graduates from four subsequent editions of the survey was compiled. In order to identify the predictors of graduates' success, a logistic regression model was applied.

The study reveals that graduates' success in the labour market is influenced not only by their discipline, but also by the activities undertaken during their studies, the type of studies and demographic features. Studies in natural sciences give chance for higher earnings, job matching and satisfaction. The humanities and social sciences increase only graduates’ group satisfaction. The impact of activities during studies is diversified – those matched to studies increase the job matching and those unmatched lower the earnings, job matching and satisfaction. Parents' level of education resulted in salary increase. The results also confirm the premises of behavioural theory.

Firstly, the main research limitation is that data of one particular university's graduates are used, so the results should be interpreted in the context of Poland only. Secondly, the authors propose a precise concept of success; however, it could be refined in any future study. This limitation could be mitigated by the flexibility of the model, which guarantees that other predictors of success could be involved. Furthermore, the article was based on data collected before the COVID-19 pandemic, when the labour market was completely different, so it also could be revised now.

The results of the analysis can be used when preparing the University’s educational offer. Since various predictors are implemented in the model, the information could be useful not only for future students, but also for current students, so they can make a more data-driven decision about their future careers. Additionally, University careers’ advisors are provided with knowledge on the determinants of graduates' success. Taking a broader view, the research findings are also informative for labour market institutions.

The paper offers an advanced analysis in a field that is under-researched in many transition countries, including Poland, i.e. graduates' entry into the workplace. Although the study provides insight into the factors that determine the labour market success of one particular university's graduates, this modelling can be applied to the empirical data of another higher education institution’s (HEI's) graduates.

The purpose of this paper is to deal with a decision‐making problem in a complex operation system. Two levels of the system are made up of two different decision problems, i.e. task scheduling and task execution where by the latter an executor's movement control problem is understood. Interconnection of both levels creates a new problem that requires a new solution algorithm.

With use of a model of a moving vehicle in the state space, an offline movement control algorithm, is developed. Moreover, the concept of rescheduling to improve the solution through repeated execution of both, the movement control and the scheduling algorithms is used.

Decision‐making problem, and its substitutive version is defined. A solution is given for the substitutive approach along with its analytical evaluation. Furthermore, significant improvement of the solution through rescheduling has been achieved.

Proposed approach to decision making creates a difficulty for generalization of the results on cases with a different movement model.

The methodology introduced in the paper can be applied prominently in flexible manufacturing systems with moving executors where it is either unfeasible to move the assemblage or the executors are capable of performing multiple tasks.

Solution to a decision‐making problem in a two‐level system, with the given vehicle model, and use of rescheduling for quality improvement was not considered beforehand.

This study evaluates the economic effectiveness of higher education in Lithuania by measuring returns to investment in higher education for both individual university graduates and the state, particularly aiming to discover how higher education investments impact economic returns at both micro (individual) and macro (national) levels.

A dual methodological approach has been applied, utilizing both the Mincer earnings equation and the full discounting method, to draw a clear distinction between the returns enjoyed by individuals and those accrued to the country. Calculations for individual economic returns are done using the most recent available Lithuanian Department of Statistics data on the wage structure, while national return on education was based on the State Tax Inspectorate and Lithuanian Public Finance databases.

The research confirms that Lithuanian investments in education positively influence both individual earnings and society at large, mainly due to the low cost of education and the high returns. For individuals, net present value varies from €126,000 to €224,000, and the internal rate of return is from 7% to 46%, with the highest return being for males working in companies of 50–249 employees and holding a bachelor’s degree. It is also noteworthy that one additional year spent in education increases earnings on average by 4.1%. The financing of first cycle studies costs the state two times less than second and third cycle studies. For this reason, the net present value (NPV) and internal rate of return (IRR) of first cycle studies are higher than those of second and third cycle studies.

While higher education is generally and globally seen as a way to ensure financial stability and career advancement at the individual level and socioeconomic development at the national one, the question of cost versus benefits at both levels is principal and diachronic. Our research quantifies the NPV and IRR of education investments and highlights the differential economic returns of various education levels, where policymakers can utilize these insights to inform strategic decisions regarding education funding and resource allocation. This study, therefore, provides explicit quantitative answers and presents individuals and policymakers with tangible results and practicable direction in their decision-making. The findings are applicable to the specific country-focus, but also constitute an applicable case study in the international context, particularly for European and other countries of comparable economic structure and developmental stage.