An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem

被引:92
作者
Wang, Ling [1 ]
Fang, Chen [1 ]
机构
[1] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol TNList, Dept Automat, Beijing 100084, Peoples R China
基金
美国国家科学基金会;
关键词
Multi-mode resource-constrained project scheduling; Estimation of distribution algorithm; Probability model; Permutation based local search; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; LOCAL SEARCH; MULTIPLE-MODES;
D O I
10.1016/j.cor.2011.05.008
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, an estimation of distribution algorithm (EDA) is proposed to solve the multi-mode resource-constrained project scheduling problem (MRCPSP). In the EDA, the individuals are encoded based on the activity-mode list (AML) and decoded by the multi-mode serial schedule generation scheme (MSSGS), and a novel probability model and an updating mechanism are proposed for well sampling the promising searching region. To further improve the searching quality, a multi-mode forward backward iteration (MFBI) and a multi-mode permutation based local search method (MPBLS) are proposed and incorporated into the EDA based search framework to enhance the exploitation ability. Based on the design-of-experiment (DOE) test, suitable parameter combinations are determined and some guidelines are provided to set the parameters. Simulation results based on a set of benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed EDA. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:449 / 460
页数:12
相关论文
共 31 条
[1]   An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering [J].
Aickelin, U. ;
Burke, E. K. ;
Li, J. .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2007, 58 (12) :1574-1585
[2]   Solving the multi-mode resource-constrained project scheduling problem with genetic algorithms [J].
Alcaraz, J ;
Maroto, C ;
Ruiz, R .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2003, 54 (06) :614-626
[3]  
[Anonymous], 2006, NEW EVOLUTIONARY COM
[4]   A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version [J].
Bouleimen, K ;
Lecocq, H .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2003, 149 (02) :268-281
[5]   Inexact graph matching for model-based recognition:: Evaluation and comparison of optimization algorithms [J].
Cesar, RM ;
Bengoetxea, E ;
Bloch, I ;
Larrañaga, P .
PATTERN RECOGNITION, 2005, 38 (11) :2099-2113
[6]   Differential evolution for solving multi-mode resource-constrained project scheduling problems [J].
Damak, N. ;
Jarboui, B. ;
Siarry, P. ;
Loukil, T. .
COMPUTERS & OPERATIONS RESEARCH, 2009, 36 (09) :2653-2659
[7]   A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem [J].
Elloumi, Sonda ;
Fortemps, Philippe .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 205 (01) :31-41
[8]   Project scheduling with multiple modes: A genetic algorithm [J].
Hartmann, S .
ANNALS OF OPERATIONS RESEARCH, 2001, 102 (1-4) :111-135
[9]   A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems [J].
Jarboui, B. ;
Damak, N. ;
Siarry, P. ;
Rebai, A. .
APPLIED MATHEMATICS AND COMPUTATION, 2008, 195 (01) :299-308
[10]   An estimation of distribution algorithm for minimizing the total flowtime in permutation flowshop scheduling problems [J].
Jarboui, Bassem ;
Eddaly, Mansour ;
Siarry, Patrick .
COMPUTERS & OPERATIONS RESEARCH, 2009, 36 (09) :2638-2646