The relationship between systems development and systems methodologies is discussed in this paper. As the measure of system development on the macro level, Gross Domestic Product (GDP) is assumed to be the consequence of systems Research and Development (R&D), which is estimated indirectly by the number of published articles in the last 40 years. It was supposed that profit and governmental organizations are systems comprised of Production, Management and Information Systems (IS), and that their quality performance is related with its income generation, which in the future would impact the overall GDP of a country. Under such view, we also assume that such organizational processes are qualitatively improved by the application of knowledge generated by research publications, and in this study, we research for the specific case of the Systems Approach (SA), Systems Engineering (SE), Operational Research (OR), Information Systems Development (ISD) and Simulation, as the research topics for coping with organizational improvement. We looked for the articles containing the afore-mentioned variables as topic keywords, which indicate sufficient correlations with GDP and carrying information on sustainable development. We found a positive trend in the evolution of research methodologies, such as SE, ISD and OR, towards a Systems Approach and Simulation as a holistic methodology. As a result, we have proved the dynamic hypothesis of a high correlation between GDP of Top 10 + Slovenia and R&D expressed by the above-mentioned variables.
This article describes the development of a web-based dynamic job-shop scheduling system for small and medium enterprises. In large enterprises, scheduling is mainly performed with appropriate technology by human experts; many small and medium enterprises lack the resources to implement such a task. The main objective was to develop a cost-effective, efficient solution for job-shop scheduling in small and medium enterprises with an emphasis on accessibility, platform independence and ease of use. For these reasons, we decided to develop a web-based solution with the main emphasis on the development of an intelligent and dynamic user interface. The solution is built upon modular programming principles and enables dynamic scheduling on the basis of artificial intelligence, i.e. genetic algorithms. The solution has been developed as a standalone information system, which allows the management of virtually all scheduling activities through an administration panel. In addition, the solution covers the five main functionalities that completely support the scheduling process, i.e. making an inventory of resources available in the company, using it in the process of production planning, collecting data on production activities, distribution of up-to-date information and insight over events in the system.
Background: The sugar beet is the main field crop used for sugar production in the temperate climatic zone. The abolishment of the quota system will open new investment opportunities in countries that were forced to abandon sugar industry as the result of the reform in 2006. Present paper describes the modeling of sugar beet production and its processing into sugar for purpose of decision support. Methods: A system dynamics methodology was chosen to model impacts of regional sugar factory investment. We present two basic concepts of system dynamics models at causal loop diagram level. The first holistic model deals with regional planning of new product development and the second one deals with factory model. Results: The holistic model presented main feedback loops and dynamics of main elements in the case of regional investment into sugar industry. The factory model considered the specifics of the beet processing which is a) limited period of beet processing and b) initial adjustment to the production capacity at the start of the production season Conclusions: The model seeks answers to strategic questions related to the whole sugar beet production and processing system and will be used for simulation of different scenarios for sugar production and their impact on economic and environmental parameters at an aggregate level.
We discuss the concept of simulation and its application in the resolution of problems in complex industrial systems. Most problems of serious scale, be it an inventory problem, a production and distribution problem, a management of resources or process improvement, all real world problems require a mix of generic, data algorithmic and Ad-hoc solutions making the best of available information. We describe two projects in which analytical solutions were applied or contemplated. The first case study uses linear programming in the optimal allocation of advertising resources by a major internet service provider. The second study, in a series of projects, analyses options for the expansion of the production and distribution network of mining products, as part of a sensitive strategic business review. Using the examples, we make the case for the need of simulation in complex industrial problems where analytical solutions may be attempted but where the size and complexity of the problem forces a Monte Carlo approach.
Background and Purpose: The sugar beet is the main field crop used for sugar production in the temperate climatic zone. Since investment in sugar beet industry are long term and ireversible the decision support and economic analysis are required in order to maximise investment returns. Methodology: A system dynamics methodology was chosen to model the impacts of regional sugar factory investments. We present the basic concepts of system dynamics (SD) models and their development in the case of sugar beet production and processing systems. Sugar beet economics are also analyzed using the static technological economic simulation model. Results: The simulation provides answers to strategic questions related to the total sugar beet production and processing system and will be used for the simulation of different scenarios for sugar production and their impact on economic and environmental parameters at an aggregate level. Furthermore, the feasibility analysis of sugar beet production revealed that at the current price and intensity levels (yields), we can expect profitable sugar beet production for both white sugar and ethanol. Conclusion: Preliminary results show that under expected production parameters the sugar beet processing and production would be economically feasible.
This paper presents the problem of auniform scheduling domain description. It was established that the algorithm used for scheduling is general, disregarding the type of scheduling domain. On the basis of five different scheduling domains, a general description model was developed. The research is focused on the programming application of the resource scheduling model, presented as a UML class diagram. Diverse meta-languages for the model description were considered. Of these XML, an EAV model and object oriented languages have shown to be the most effective. Even though Java is not widely used as a description language, it has proved effective as a meta-language for the description of the extensible scheduling model.
This paper presents the system dynamics model of organic farming development in order to support decision making. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long-term dynamic context. The model will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level. Using the model, several policy scenarios were performed.
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