Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation

This work proposes a binary nonlinear bi-objective optimization model for the problem of planning the sustainable cultivation of crops. The solution to the problem is a planting schedule for crops to be cultivated in predefined plots, in order to minimize the possibility of pest proliferation and maximize the profit of this process. Biological constraints were also considered. Exact methods, based on the nonlinear model and on a linearization of that model were proposed to generate Pareto optimal solutions for the problem of sustainable cultivation, along with a metaheuristic approach for the problem based on a genetic algorithm and on constructive heuristics. The methods were tested using semi-randomly generated instances to simulate real situations. According to the experimental results, the exact methodologies performed favorably for small and medium size instances. The heuristic method was able to potentially determine Pareto optimal solutions of good quality, in a reduced computational time, even for high dimension instances. Therefore, the mathematical models and the methods proposed may support a powerful methodology for this complex decision-making problem.

Automated summary

This work proposes a binary nonlinear bi-objective optimization model for planning the sustainable cultivation of crops. Exact methods and a metaheuristic approach were proposed and tested, showing their effectiveness in finding high-quality solutions for small and medium size instances. The proposed mathematical models and methods provide a powerful methodology for this complex decision-making problem.