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Transport autonomiczny jako element strategii miasta zrównoważonego

100%
Jurczak M., Pawlicka K.
Studia Miejskie
|
2023
|
vol. 45
58-73
EN
The article contains the identification and characteristics of the relationship between the development of autonomous transport and building a sustainable city strategy. Innovative transport solutions are becoming more and more important in debates on shaping the development of sustainable cities. However, currently there are no structured urban policies combining the two issues. Hence, the aim of this article is to identify the possibilities of creating the development of autonomous mobility based on the sustainable development strategy of the city. The research problem is to determine how the city's sustainable development strategy can affect the development of autonomous mobility. For the purposes of the study, biggest Polish cities were analyzed.
PL
W artykule dokonano identyfikacji i określenia charakterystyki związku pomiędzy rozwojem transportu autonomicznego w mieście a budowaniem zrównoważonej strategii miasta. Innowacyjne rozwiązania transportowe stają się coraz ważniejszym elementem w debacie na temat rozwoju zrównoważonych miast. Niestety obecnie nie ma ustrukturyzowanej polityki miejskiej w tym obszarze. Celem artykułu jest przedstawienie sposobów kształtowania autonomicznej mobilności w oparciu o strategię zrównoważonego rozwoju miasta. Problemem badawczym poruszonym w artykule jest wpływ strategii zrównoważonego rozwoju miasta na rozwój autonomicznej mobilności. Dodatkowo wskazano wybrane wnioski z badania ankietowego, przeprowadzonego w polskich miastach.
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Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA

81%
Jurczak M., Miebs G., Bachorz R. A.
Operations Research and Decisions
|
2022
|
vol. 32
|
issue 4
EN
The main objective of this paper is to present an example of the IT system implementation with advanced mathematical optimisation for job scheduling. The proposed genetic procedure leads to the Pareto front, and the application of the multiple criteria decision aiding (MCDA) approach allows extraction of the final solution. Definition of the key performance indicator (KPI), reflecting relevant features of the solutions, and the efficiency of the genetic procedure provide the Pareto front comprising the representative set of feasible solutions. The application of chosen MCDA, namely elimination et choix traduisant la réalité (ELECTRE) method, allows for the elicitation of the decision maker (DM) preferences and subsequently leads to the final solution. This solution fulfils all of the DM expectations and constitutes the best trade-off between considered KPIs. The proposed method is an efficient combination of genetic optimisation and the MCDA method.
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