期刊
ENGINEERING WITH COMPUTERS
卷 34, 期 3, 页码 621-635出版社
SPRINGER
DOI: 10.1007/s00366-017-0562-6
关键词
Firefly algorithm; Greedy optimization algorithm; Dynamic optimization; Knapsack problem
资金
- National Natural Science Foundation of China [61503165, 61402207, 61673196, 61772225]
- Natural Science Foundation of Jiangsu Province [BK20150239]
- National Natural Science Fund for Distinguished Young Scholars of China [61525304]
In this paper, a novel global firefly algorithm (GFA) is proposed for solving randomized time-varying knapsack problems (RTVKP). The RTVKP is an extension from the generalized time-varying knapsack problems (TVKP), by dynamically changing the profit and weight of items as well as the capacity of knapsack. In GFA, two-tuples which consists of real vector and binary vector is used to represent the individual in a population, and two principal search processes are developed: the current global best-based search process and the trust region-based search process. Moreover, a novel and effective two-stage repair operator is adopted to modify infeasible solutions and optimize feasible solutions as well. The performance of GFA is verified by comparison with five state-of-the-art classical algorithms over three RTVKP instances. The results indicate that the proposed GFA outperform the other five methods in most cases and that GFA is an efficient algorithm for solving randomized time-varying knapsack problems.
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