A hybrid projection method for resource-constrained project scheduling problem under uncertainty

被引:3
作者
Aramesh, Saeed [1 ]
Aickelin, Uwe [2 ]
Khorshidi, Hadi Akbarzadeh [2 ]
机构
[1] Shahed Univ, Fac Engn, Dept Ind Engn, Tehran, Iran
[2] Univ Melbourne, Sch Comp & Informat Syst, Melbourne, Vic 3010, Australia
关键词
RCPSP; Projection measure; Buffer; IVF; Group decision-making; Expert weighting; TIME/RESOURCE TRADE-OFF; GROUP DECISION-MAKING; OPTIMIZATION; AGGREGATION; MANAGEMENT; HEURISTICS; FRAMEWORK; NUMBERS; MODELS; IDEAL;
D O I
10.1007/s00521-022-07321-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Resource constraint project scheduling problem (RCPSP) is one of the most important problems in the scheduling environment. This paper introduces a new framework to collect the activities' duration and resource requirement by group decision-making, solve the RCPSP with variable durations, and obtain the buffer to protect the schedule. Firstly, the duration and resources of the project's activities are determined by a new expert weighting method. In the group decision-making, hybrid projection measure is introduced to construct the aggregated decision about some RCPSP parameters. The hybrid projection includes the projection, normalized projection, and bi-directional projection. In the second step, a RCPSP model is presented where the duration of activities can change within certain intervals. Thus, the problem is called the RCPSP with variable durations. The intervals for activities' duration and resource requirements are obtained from the group decision-making in the first step. Genetic algorithm and vibration damping optimization are applied to solve the RCPSP with variable durations. In the third step, the project's buffer is determined to protect the schedule. In this step, the intervals for activities' duration are converted into interval-valued fuzzy (IVF) numbers and the buffer sizing method is extended using IVF numbers. Finally, the presented framework is solved for a practical example and the results are reported.
引用
收藏
页码:14557 / 14576
页数:20
相关论文
共 58 条
[1]   A Neurogenetic approach for the resource-constrained project scheduling problem [J].
Agarwal, Anurag ;
Colak, Selcuk ;
Erenguc, Selcuk .
COMPUTERS & OPERATIONS RESEARCH, 2011, 38 (01) :44-50
[3]  
Al-Subhi Al-Harbi K. M., 2001, International Journal of Project Management, V19, P19, DOI 10.1016/S0263-7863(99)00038-1
[4]  
Alizdeh Samira, 2020, International Journal of Advanced Intelligence Paradigms, V16, P4
[5]   Priority-based heuristics for the multi-skill resource constrained project scheduling problem [J].
Almeida, Bernardo F. ;
Correia, Isabel ;
Saldanha-da-Gama, Francisco .
EXPERT SYSTEMS WITH APPLICATIONS, 2016, 57 :91-103
[6]  
Altarazi FM, 2017, MULTIMODE RESOURCE C
[7]  
Aramesh S, 2021, IRAN J FUZZY SYST, V18, P151
[8]   A soft computing approach based on critical chain for project planning and control in real-world applications with interval data [J].
Aramesh, S. ;
Mousavi, S. M. ;
Mohagheghi, V ;
Zavadskas, E. K. ;
Antucheviciene, J. .
APPLIED SOFT COMPUTING, 2021, 98
[9]   Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets [J].
Ashtiani, Behzad ;
Haghighirad, Farzad ;
Makui, Ahmad ;
Montazer, Golam Ali .
APPLIED SOFT COMPUTING, 2009, 9 (02) :457-461
[10]   Fuzzy resource-constrained project scheduling using taboo search algorithm [J].
Atli, Omer ;
Kahraman, Cengiz .
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2012, 27 (10) :873-907