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论文类型：期刊论文

第一作者：Chen, Wang

通讯作者：Shi, YJ (reprint author), Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China.

合写作者：Shi, Yan-jun,Teng, Hong-fei,Lan, Xiao-ping,Hu, Li-chen

发表时间：2010-03-15

发表刊物：INFORMATION SCIENCES

收录刊物：SCIE、EI

卷号：180

期号：6,SI

页面范围：1031-1039

ISSN号：0020-0255

关键字：Project management; Scheduling; Ant colony optimization; Scatter search; Project scheduling

摘要：We propose an efficient hybrid algorithm, known as ACOSS, for solving resource-constrained project scheduling problems (RCPSP) in real-time The ACOSS algorithm combines a local search strategy. ant colony optimization (ACO), and a scatter search (SS) in an iterative process In this process, ACO first searches the Solution Space and generates activity lists to provide the initial population for the SS algorithm. Then, the SS algorithm builds a reference set from the pheromone trails of the ACO, and improves these to obtain better solutions Thereafter, the ACO uses the improved solutions to update the pheromone set. Finally in this iteration, the ACO searches the solution set using the new pheromone trails after the SS has terminated In ACOSS, ACO and the SS share the solution space for efficient exchange of the Solution set The ACOSS algorithm is compared with state-of-the-art algorithms using a set of standard problems available in the literature The experimental results validate the efficiency of the proposed algorithm (C) 2009 Elsevier Inc All rights reserved.