The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
With the rapid development of Information Technology (IT) in recent past, number of unsolved real-world complex problems benefited immensely since solutions could be found within considerable time period. This is mainly due to the computational intelligence techniques which can deliver a reasonably good result within a shorter time period by performing complex calculations with numbers of iterations. Distribution operation is a common problem in the area of supply chain management which got the attention for many years. However, up to now only simplified versions of distribution operations such as Vehicle Routing Problem (VRP), Travelling Salesman Problem (TSP) have being considered by many researches. Some of the researchers adopted with heuristic approaches such as Simulated Annealing (SA), Genetic Algorithm (GA), Tabu Search (TS) and etc. with number of assumptions. However, the standard problems are far away from the real world problem. Furthermore, when the problem size (or scale) increases, the computational time to finds the optimal results increase exponentially, hence these problems are categorized as NP-hard problems in mathematical terms. To bridge the gap between standard problems in distribution and the real world problems, in this research, the standard VRP problem is extended to multi depot environment with split delivery option and tries to investigate the applicability of Simulated Annealing (SA) and Tabu Search (TS) to find solutions to this complex problem within considerable time frame. Numbers of simulation studies are carried out with both of these techniques and results revealed that both these techniques can be adapted to complex Multi Depot Vehicle Routing Problem with Time Windows and Split Delivery (MDVRPTWSD) problem and TS out performances in solution quality.
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