2016
DOI: 10.1007/s40092-016-0148-8
|View full text |Cite
|
Sign up to set email alerts
|

Multi-objective optimization of discrete time–cost tradeoff problem in project networks using non-dominated sorting genetic algorithm

Abstract: The time-cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving the project cash flow, avoiding unfavorable weather conditions, compensating the delays, and so on. Since there is a need to allocate extra resources to short the finishing time of project and the project managers are intended to spend the lowest possib… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
12
0

Year Published

2017
2017
2024
2024

Publication Types

Select...
5
5

Relationship

0
10

Authors

Journals

citations
Cited by 35 publications
(12 citation statements)
references
References 33 publications
0
12
0
Order By: Relevance
“…In multiobjective optimization problems, nondominated sorting genetic algorithm (NSGA II) is often used to achieve the Pareto front and a set of optimal solutions can be obtained. e results showed that this method can help construction planners achieve all the projects' multiple objectives under certain limits [21,30]. GA is an efficient method to obtain an optimal or a set of optimal solutions in construction scheduling.…”
Section: Metaheuristic Methodsmentioning
confidence: 97%
“…In multiobjective optimization problems, nondominated sorting genetic algorithm (NSGA II) is often used to achieve the Pareto front and a set of optimal solutions can be obtained. e results showed that this method can help construction planners achieve all the projects' multiple objectives under certain limits [21,30]. GA is an efficient method to obtain an optimal or a set of optimal solutions in construction scheduling.…”
Section: Metaheuristic Methodsmentioning
confidence: 97%
“…In the construction process, whether building materials or labor force are disposable, different types of construction projects have different plans, and plans are also disposable. There is basically no case of modifying the plan after half of the construction according to the plan, so it needs to perform reasonable optimization allocation on the projects in the construction planning [2]. The main objectives of management optimization of construction projects are construction period, cost and quality, and the relevance between the optimization objectives is high.…”
Section: Introductionmentioning
confidence: 99%
“…Cheng et al (2014) integrated the fuzzy C-means clustering technique and the chaotic technique into the differential evolution (DE) algorithm to develop the fuzzy clustering chaoticbased differential evolution (FCDE) algorithm. Shahriari (2016) presented the existing meta-heuristic solution procedures to solve the multi-mode resource-constrained project scheduling problem. Messelis and De Causmaecker (2014) investigated the construction of an automatic algorithm selection tool for the MMRCPSP.…”
Section: Introduction and Literature Reviewmentioning
confidence: 99%