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Decision making in the Agriculture domain can be a complex task. The landarea allocated to each crop should be fixed every season according to severalparameters: prices, demand, harvesting periods, seeds, ground, season etc...The decision to make becomes more difficult when a group of farmers must fixthe price and all parameters all together. Generally, optimization models areuseful for farmers to find no dominated solutions, but it remains difficult ifthe farmers have to agree on one solution. We combine two approaches in orderto 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 centralizedoptimization model. Based on this set of solution we then used a Group DecisionSupport System called GRUS for choosing the best solution for the group offarmers. The combined approach allows us to determine the best solution for thegroup in a consensual way. This combination of approaches is very innovativefor the Agriculture. This approach has been tested in laboratory in a previouswork. In the current work the same experiment has been conducted with realbusiness (farmers) in order to benefit from their expertise. The twoexperiments are compared.

Group Decision Support for agriculture planning by a combination of Mathematical Model and Collaborative Tool