A bi-level fuzzy random model for multi-mode resource-constrained project scheduling problem of photovoltaic power plant

被引:7
作者
Zhang, Zhe [1 ]
Liu, Ming [1 ]
Song, Xiaoling [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing 210094, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; HYBRID ALGORITHM; GENERATION; SYSTEM; TRADEOFF; DEMAND; DESIGN; CHINA;
D O I
10.1063/1.5053623
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As the largest energy consumption country, China now pays more and more attention to photovoltaic power generation because solar energy is the largest renewable and sustainable energy reserve in the world. In this case, the photovoltaic power generation plant project plays a crucial role in sustainable development, especially in the underdeveloped northwest region of China. This paper focuses on applying bi-level programing to the multimode resource-constrained project scheduling problem (MRCPSP) in photovoltaic power generation plant construction, which simultaneously considers the practical hierarchical organization structure and an uncertain decision-making environment. A bi-level fuzzy random multiple objective model is developed, wherein the government agency is in the upper decision level, while the contractor is in the lower decision level. Then, motivated by the particular mathematical nature of the proposed bi-level MRCPSP model, a hybrid intelligent algorithm is designed. Finally, a practical case from the Shenneng Futa Kashi-Tashi-Kuergan photovoltaic power generation plant project in a Chinese energy company is applied, and the results validate the practicability of the proposed model and solution algorithm for solving practical photovoltaic power plant project scheduling problems.
引用
收藏
页数:15
相关论文
共 60 条
[1]   A multi-mode resource-constrained discrete time-cost tradeoff problem solving using an adjusted fuzzy dominance genetic algorithm [J].
Afruzi, E. Nabipoor ;
Roghanian, E. ;
Najafi, A. A. ;
Mazinani, M. .
SCIENTIA IRANICA, 2013, 20 (03) :931-944
[2]  
Anderson A., 2001, 451 NCHRP
[3]   Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem [J].
Asta, Shahriar ;
Karapetyan, Daniel ;
Kheiri, Ahmed ;
Ozcan, Ender ;
Parkes, Andrew J. .
INFORMATION SCIENCES, 2016, 373 :476-498
[4]   SOME PROPERTIES OF THE BILEVEL PROGRAMMING PROBLEM [J].
BARD, JF .
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 1991, 68 (02) :371-378
[5]   Multi-mode resource constrained multi-project scheduling and resource portfolio problem [J].
Besikci, Umut ;
Bilge, Umit ;
Ulusoy, Gunduz .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 240 (01) :22-31
[6]   A heuristic approach for resource constrained project scheduling with uncertain activity durations [J].
Bruni, M. E. ;
Beraldi, P. ;
Guerriero, F. ;
Pinto, E. .
COMPUTERS & OPERATIONS RESEARCH, 2011, 38 (09) :1305-1318
[7]   Resource constrained project scheduling with uncertain activity durations [J].
Chakrabortty, Ripon K. ;
Sarker, Ruhul A. ;
Essam, Daryl L. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 112 :537-550
[8]   The particle swarm - Explosion, stability, and convergence in a multidimensional complex space [J].
Clerc, M ;
Kennedy, J .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (01) :58-73
[9]   On the formalization of fuzzy random variables [J].
Colubi, A ;
Dominguez-Menchero, JS ;
López-Díaz, M ;
Ralescu, DA .
INFORMATION SCIENCES, 2001, 133 (1-2) :3-6
[10]   A genetic algorithm-based method for look-ahead scheduling in the finishing phase of construction projects [J].
Dong, Ning ;
Ge, Dongdong ;
Fischer, Martin ;
Haddad, Zuhair .
ADVANCED ENGINEERING INFORMATICS, 2012, 26 (04) :737-748