Bir çevrimiçi eğitim web sitesinin genelleştirilmiş atama problemine yönelik metasezgisel yaklaşımlar

BinYaprak is a TurkishWIN (Turkish Women's International Network) initiative that offers role model stories for inspiration, educational content, real-life stories and a networking platform through online and offline events. BinYaprak online education website aims to create ways for content and network aggregation between experts and learners for the ease of knowledge discovery. Experts are the people who join the platform for free in order to share their knowledge and experience with interested learners. Learners join the platform for free to learn new skills, access new networks, and find out new jobs and opportunities. Thus, this study aims to provide an assignment of a learner to an expert which satisfies both sides as much as possible. An expert can be assigned to more than one learner ensuring each learner is assigned at most one expert subject to each expert's capacity, thus the problem becomes a generalized assignment (GAP) which is known as an NP-Hard problem. In this study, we present a new implementation of a nature-inspired metaheuristic algorithm called Migrating Birds Optimization (MBO) and a hybrid of Simulated Annealing (SA) and Tabu Search (TS) methods in order to solve the GAP of BinYaprak online education website. In our computational study, we tested both MBO and hybrid SA/TS on small and large-sized instances of GAP of BinYaprak website. Also, we used Gurobi Python API as a baseline reference against which we can compare our heuristic methods' performances. Our numerical analyzes show that the hybrid SA/TS outperforms the MBO in terms of solution quality and computational effort, hence hybrid SA/TS can be used in practice to obtain high quality solutions.