Group Decision Support for agriculture planning by a combination of Mathematical Model and Collaborative Tool
This addresses the challenge of collaborative decision-making among farmers in agriculture, though it appears incremental as it builds on prior laboratory work by extending it to real-world scenarios.
The paper tackles the problem of group decision-making for agricultural planning by combining a centralized optimization model to generate non-dominated solutions with a Group Decision Support System (GRUS) to help farmers agree on a consensual best solution, and it compares laboratory experiments with real-world tests involving farmers.
Decision making in the Agriculture domain can be a complex task. The land area allocated to each crop should be fixed every season according to several parameters: prices, demand, harvesting periods, seeds, ground, season etc... The decision to make becomes more difficult when a group of farmers must fix the price and all parameters all together. Generally, optimization models are useful for farmers to find no dominated solutions, but it remains difficult if the farmers have to agree on one solution. We combine two approaches in order to support a group of farmers engaged in this kind of decision making process. We firstly generate a set of no dominated solutions thanks to a centralized optimization model. Based on this set of solution we then used a Group Decision Support System called GRUS for choosing the best solution for the group of farmers. The combined approach allows us to determine the best solution for the group in a consensual way. This combination of approaches is very innovative for the Agriculture. This approach has been tested in laboratory in a previous work. In the current work the same experiment has been conducted with real business (farmers) in order to benefit from their expertise. The two experiments are compared.