Improved Quantum-Inspired Tabu Search Algorithm for Solving Function Optimization Problem
Yi-Jyuan Yang, Shu–Yu Kuo, Fang-Jhu Lin, I.-I Liu, Yao–Hsin Chou · 2013
After we read the paper about quantum-inspired tabu search algorithm (QTS) for solving 0/1 knapsack problems [5], we got many ideas. In this study, we proposed a method which is called improved quantum-inspired tabu search algorithm (IMQTS). In IMQTS, we add two skills in QTS. First, we add the probability of taking a worse solution become the guide of updating the populations. Second, we add a second rotation which is turning possible solutions away from the worst solution. We use IMQTS for solving function optimization problem to show its performance. The experiment results show that IMQTS performs well in function optimization problem, and IMQTS would not fall into local optimum.