Prof. Yun (Amy) Lu
Kutztown University of PA, USA
Improved Teaching-Learning-Based Optimization Metaheuristic for Multiple-Choice Multidimensional Knapsack Problems
In this paper, we improve the performance of the teaching-learning-based optimization (TLBO) method by introducing 'teacher training' before the teaching phase of TLBO. That is, before the teaching phase of TLBO, we perform a local neighbourhood search on the best solution (the teacher) in the current population. The effectiveness of teacher training (TT) in terms of both solution quality and convergence rate will be demonstrated by using this approach (TT-TLBO) to solve a large (393) number of problem instances from the literature for the important (NP-Hard) multiple-choice multidimensional knapsack problem (MMKP). Furthermore, we will demonstrate that TLBO outperforms the best published solution approaches for the MMKP.
Yun Lu received an MA in Computer Science and a PhD in Mathematics from Wesleyan University in 2006 and 2007, respectively. She is currently a Professor in the Department of Mathematics at Kutztown University. Her research interests include optimization, algorithms, mathematical logic, graph theory, and bioinformatics.