title: A novel harmony search algorithm based on teaching-learning strategies for 0-1 knapsack problems.
abstract: To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems.
authors.affiliation: School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China.
authors.forename: Shouheng
authors.initials: S
authors.lastname: Tuo
authors.affiliation: School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China.
authors.forename: Longquan
authors.initials: L
authors.lastname: Yong
authors.affiliation: School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China.
authors.forename: Fang'an
authors.initials: F
authors.lastname: Deng
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D057386:Search Engine / Q000379:methods*