Multi Objective Mixed Integer Nonlinear Optimization Based on PSO with Application to Integrated Weed Management
Keywords:
optimization, PSO, MINLP-MO, Integrated Weed ManagementAbstract
An optimization tool for solving nonlinear multi-objective mixed-integer problems is presented. The algorithm is based on the particle swarm metaheuristic (PSO). As PSO was designed to be applied to box-constrained continuous problems, a technique based on the total of the violations of the restrictions of each particle was incorporated to address restricted problems of the general type. Additionally, to treat binary variables, the "Angle Modulation" method was adopted, which trough the inclusion of four additional continuous variables and the evaluation of a trigonometric function, generates the values of all the binaries along the search. Finally, to address multi-objective problems, a methodology was incorporated to identify the Pareto front. The developed algorithm was tested on different benchmark functions of two and three objectives, obtaining satisfactory results. The potential of the developed tool is illustrated through a case study of agronomic interest: the design of strategies for integrated weed management.
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Copyright (c) 2022 Lucía Damiani, Franco A. Molinari, Mariano Frutos, Guillermo R. Chantre, Aníbal M. Blanco
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