A moving block sequence-based evolutionary algorithm for resource-constrained project scheduling problems

被引:0
|
作者
Hao, Xingxing [1 ]
Liu, Jing [1 ]
Yuan, Xiaoxiao [1 ]
Tang, Xianglong [1 ]
Li, Zhangtao [1 ]
机构
[1] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ, Xian 710071, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
moving block sequence; MBS; resource-constrained project scheduling problems; RCPSPs; multiagent evolutionary algorithm; MAEA; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; SCATTER SEARCH; HEURISTICS; CLASSIFICATION; JUSTIFICATION;
D O I
10.1504/IJBIC.2019.101631
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a new representation for resource-constrained project scheduling problems (RCPSPs), namely moving block sequence (MBS), is proposed. In RCPSPs, every activity has fixed duration and resource demands, therefore, it can be modelled as a rectangle block whose height represents the resource demand and width the duration. Naturally, a project that consists of N activities can be represented as the permutation of N blocks that satisfy the precedence constraints among activities. To decode an MBS to a valid schedule, four move modes are designed according to the situations that how every block can be moved from its initial position to an appropriate location that can minimise the makespan of the project. Based on MBS, the multiagent evolutionary algorithm (MAEA) is used to solve RCPSPs. The proposed algorithm is labelled as MBSMAEA-RCPSP, and by comparing with several state-of-the-art algorithms on benchmark J30, J60, J90 and J120, the effectiveness of MBSMAEA-RCPSP is clearly illustrated.
引用
收藏
页码:85 / 102
页数:18
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