Optimization of mycelium growth using genetic algorithm for multi-objective functions - Muhamad Faiz, Abu Bakar (2019)
Optimization of mycelium growth is a process that are aim to get the optimal value for growing mushroom. Mathematical optimization was typical use for such problem, in which it was supposed to maximizing or minimizing a function. However, for optimizing mycelium growth, there are more than one function that needs to be calculated and solved, making this problem as a multi-objective optimization problem. Multi-objective optimization has become common issues discussed in many fields of study. The traditional method of the optimization requires various degree of understanding and analyzation of multiple things such as the importance of an objective against the other objectives. Trade-off between the objectives, exist for the optimization process. To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. In order to achieve such goal, several research papers related to mycelium and mushroom has been selected as part of the materials for literature review. Several papers related to genetic algorithm and objective optimization were also included. The nitrogen concentration and the mycelium extension rate of are two objectives problem that need to be solved. Through the implementation of selected multi-objective genetic algorithm, NSGA-ii was able to produce pareto front for optimizing both nitrogen concentration and the extension rate of the mycelium. Based on that result, it is concluded that multi-objective optimization problem can be solve using the applied method.