Zhang Le, Wu Jinnan
School of Information Engineering, Shenyang University, Shenyang 110044, China ; School of Information Science and Technology, Tsinghua University, Beijing 100084, China.
School of Information Engineering, Shenyang University, Shenyang 110044, China.
ScientificWorldJournal. 2014 Jan 29;2014:902950. doi: 10.1155/2014/902950. eCollection 2014.
This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.
本文研究了以最小化完工时间和总流程时间为目标的置换流水车间调度问题（PFSP），并提出了一种基于粒子群优化（PSO）的混合元启发式算法。为了增强混合元启发式算法的探索能力，引入了一种与随机可变邻域搜索相结合的模拟退火算法。为了提高混合元启发式算法的搜索多样性，提出了一种基于路径重连的解替换策略，以替换陷入局部最优的粒子。在基准实例上的计算结果表明，所提出的基于PSO的混合元启发式算法与文献中其他强大的元启发式算法具有竞争力。
