A quantum-inspired Tabu search algorithm for solving combinatorial optimization problems

• Published in: Soft computing (Berlin, Germany) Vol. 18; no. 9; pp. 1771 - 1781
• Main Authors: Chiang, Hua-Pei, Chou, Yao-Hsin, Chiu, Chia-Hui, Kuo, Shu-Yu, Huang, Yueh-Min
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2014; Springer Nature B.V
• Subjects: Artificial Intelligence; Combinatorial analysis; Computational Intelligence; Control; Cryptography; Engineering; Evolutionary algorithms; Focus; Genetic algorithms; Heuristic methods; Mathematical Logic and Foundations; Mechatronics; Neighborhoods; Optimization; Quantum computing; Qubits (quantum computing); Robotics; Search algorithms; Tabu search; Traveling salesman problem; Quantum computing; Tabu search; Combinatorial optimization; Quantum-inspired evolutionary algorithm; Knapsack problem
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-013-1203-7

In this study, we propose a novel quantum-inspired evolutionary algorithm (QEA), called quantum inspired Tabu search (QTS). QTS is based on the classical Tabu search and characteristics of quantum computation, such as superposition. The process of qubit measurement is a probability operation that increases diversification; a quantum rotation gate used to searching toward attractive regions will increase intensification. This paper will show how to implement QTS into NP-complete problems such as 0/1 knapsack problems, multiple knapsack problems and the traveling salesman problem. These problems are important to computer science, cryptography and network security. Furthermore, our experimental results on 0/1 knapsack problems are compared with those of other heuristic algorithms, such as a conventional genetic algorithm, a Tabu search algorithm and the original QEA. The final outcomes show that QTS performs much better than other heuristic algorithms without premature convergence and with more efficiency. Also on multiple knapsack problems and the traveling salesman problem QTS verify its effectiveness.