Genetic Algorithm for Web-Based Food Stand Assignment Scheduling
Abstract
Scheduling is a hard problem due to much considerations in many goals. Combination of goals in this scheduling cause the problem hard to solve even when using mathematical techniques. Optimization is a method which aim to achieve the best result with the least cost as possible. Optimization for large scale problem usually done with more modern technic, such as metaheuristic. Genetic Algorithm belongs to a larger system called Evolutionary Algorithm which is often used for solving the best value in optimization problem. Hence, this food stand assignment scheduling is build using Genetic Algorithm with population size of 50, uniform crossover with crossover rate of 0.25, mutation rate of 0.0125, and roulette wheel selection. An interview was conducted with three coordinators of fund and consumtion that results in three constraints used in building this system. Testing is done for three events and achieve mean fitness that is 87.967%, 89.609%, and 85.001% for FesTIval, TechnoFest, and DISCO, respectively.
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