stochastic programs are effective for solving long-term planning problems under uncertainty. Such programs are usually based on scenario generation model about future environment developments. In the present paper, the scenario model is developed for the case when enough data paths can be generated, but due to solvability of stochastic program the scenario tree has to be constructed. The propos...

This paper proposes a way of using scenario planning within joint interdisciplinary research programs, i.e. where industry and academia collaborate on a set of projects, to create a common mental platform which improves the understanding and collaboration within the program, gives management support and in addition results in an appealing description of the research idea from different perspect...

The intelligence analysis domain is a critical area for futures work. Indeed, analysts’ judgments of security threats are based on considerations how may unfold, and as such play vital role in informing policy- decision-making. In this domain, typically considered using qualitative scenario generation techniques the cone plausibility (CoP). We empirically examined quality scenarios generated te...

This paper presents basic principles of a scenario approach application to the problem of optimal development of social economic systems. The formalized description of scenario of system sustainable development is introduced and synergetic and attractive scenarios are examined. The modes providing stable and safe development of social economic system are investigated for synergistic scenarios, ...

Despite the recent interest in scenarios, the development of new methods and tools for Requirements Engineering integrating scenario based approaches has been limited. This paper reports on four different processes developed from research undertaken as part of the CREWS project which the authors believe will improve scenario use and make it more systematic. Furthermore CREWS aims to integrate t...

the current study investigated and compared data generation methods for groundwater modeling. thesemethods can be divided into two classes; geostatistic and probabilistic. by comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area ina grid (9-cell) format. after observing weak spatial correlation between the data, th...