A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements

The selection of sugarcane varieties is an important problem facing companies in Brazil that exploit sugarcane harvest for energy production. In the light of current concerns regarding the reduction of environmental damages and the efficiency of the production system, research into this problem is called for. In this context the authors begin by outlining the sugarcane variety selection in accordance with technical constraints with the purpose of minimizing collection and transport costs and maximizing energy obtained from residues of the sugarcane harvest. They then present a previously developed modelization for the problem within biobjective binary linear programming and study its hard computational complexity. Fundamentally, this paper is devoted to the application of a bi-objective genetic heuristic to the question addressed. A computational experiment performed using a test set including real and semi-randomly generated instances is then reported. The results prove to be very good in terms of solution quality – spacing and cardinality of the set of potentially nondominated points – besides computing time. For these reasons, this will be an appropriate tool to help sugarcane company managers to plan their producing activities. Additionally, the bi-objective genetic heuristic can be easily adapted to other binary bi-objective problems that share the assignment and the knapsack constraints with this model.