2015
DOI: 10.3934/jimo.2016.12.565
|View full text |Cite
|
Sign up to set email alerts
|

Bi-level multiple mode resource-constrained project scheduling problems under hybrid uncertainty

Abstract: This study focuses on the multi-mode resource-constrained projects scheduling problem (MRCPSP), which considers the complex hierarchical organization structure and hybrid uncertainty environment in the decision making process. A bi-level multi-objective MRCPSP model with fuzzy random coefficients and bi-random coefficients is developed for the MRCPSP. In the model, construction contractor, the upper level decision maker (ULDM), aims to minimize the consumption of resources and maximize the quality level of pro… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
4
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 13 publications
(5 citation statements)
references
References 37 publications
1
4
0
Order By: Relevance
“…Similar conclusions can be drawn from other review papers by Habibi, et al [44] and Kolisch and Hartmann [45]. Nature inspired metaheuristic algorithms such as (GA) [46], PSO [47], fruit-fly optimization algorithm [48] and SA [49] are a few of many approaches for solving SRCPSPs or uncertainty-based PSPs.…”
Section: A Existing Research On Srcpspsupporting
confidence: 77%
“…Similar conclusions can be drawn from other review papers by Habibi, et al [44] and Kolisch and Hartmann [45]. Nature inspired metaheuristic algorithms such as (GA) [46], PSO [47], fruit-fly optimization algorithm [48] and SA [49] are a few of many approaches for solving SRCPSPs or uncertainty-based PSPs.…”
Section: A Existing Research On Srcpspsupporting
confidence: 77%
“…The BLPSO algorithm has been utilized in many supply chain models, providing effective solutions for combined pricing and strategic sourcing strategies [36]. Research has demonstrated that it has exceptional search performance and rapid convergence, rendering it a highly useful instrument for addressing bi-level optimization problems in supply chain management [37]. Moreover, the simulation findings indicate that the large-scale BLPSO method has enhanced stability and supremacy when it comes to tackling supply chain optimization challenges [38].…”
Section: Discussionmentioning
confidence: 99%
“…Chen and Weng [25], and Ghoddousi et al [13] used GA to optimize time-cost trade-off for a simplified warehouse construction project. Zhang and Xu [26] minimized makespan (at the same time maximizing quality) of the hydropower plant using PSO algorithm. The same case has been optimized in terms of time, cost and quality, by Xu and Feng, with the use of hybrid algorithm [27].…”
Section: Literature Reviewmentioning
confidence: 99%