Application of Time-Cost-Quality Tradeoff Optimization Model Based on Improved PSO Algorithm to Construction Project

2009 ◽  
Author(s):  
Qin Yang
Keyword(s):  
Optimization Model ◽  
Construction Project ◽  
Pso Algorithm ◽  
Time Cost ◽  
Model Based ◽  
Improved Pso

An IES Comprehensive Profit Model Based On Improved PSO Algorithm

2019 ◽  
Author(s):  
Chen Chen ◽  
Bingjie Li ◽  
Wei Zhang ◽  
Hongda Zhao ◽  
Ciwei Gao ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Profit Model ◽  
Model Based ◽  
Improved Pso

A novel model based on wavelet LS-SVM integrated improved PSO algorithm for forecasting of dissolved gas contents in power transformers

2018 ◽  
Vol 155 ◽  
pp. 196-205 ◽  
Author(s):  
Hanbo Zheng ◽  
Yiyi Zhang ◽  
Jiefeng Liu ◽  
Hua Wei ◽  
Junhui Zhao ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Power Transformers ◽  
Dissolved Gas ◽  
Model Based ◽  
Novel Model ◽  
Improved Pso

A steel property optimization model based on the XGBoost algorithm and improved PSO

2020 ◽  
Vol 174 ◽  
pp. 109472 ◽  
Author(s):  
Kai Song ◽  
Feng Yan ◽  
Ting Ding ◽  
Liang Gao ◽  
Songbao Lu
Keyword(s):  
Optimization Model ◽  
Model Based ◽  
Steel Property ◽  
Improved Pso

Time–cost–quality trade-off analysis for planning construction projects

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tianqi Wang ◽  
Moatassem Abdallah ◽  
Caroline Clevenger ◽  
Shahryar Monghasemi
Keyword(s):  
Optimization Model ◽  
Construction Projects ◽  
Present Model ◽  
Construction Project ◽  
Time Cost ◽  
Trade Off ◽  
Content Type ◽  
Project Duration ◽  
Trade Offs ◽  
Project Objectives

Purpose Achieving project objectives in constructionprojects such as time, cost and quality is a challenging task. Minimizing project cost often results in additional project duration and might jeopardize quality, and minimizing project duration often results in additional cost and might jeopardize quality. Also, increasing construction quality often results in additional cost and time. The purpose of this paper is to identify and analyze trade-offs among the project objectives of time, cost and quality. Design/methodology/approach The optimization model adopted a quantitative research method and is developed in two main steps formulation step that focuses on identifying model decision variables and formulating objective functions, and implementation step that executes the model computations using multi-objective optimization of Non-Dominated Sorting Genetic Algorithms to identify the aforementioned trade-offs, and codes the model using python. The model performance is verified and tested using a case study of construction project consisting of 20 activities. Findings The model was able to show practical and needed value for construction managers by identifying various trade-off solutions between the project objectives of time, cost and quality. For example, the model was able to identify the shortest project duration at 84 days while keeping cost under $440,000 and quality higher than 85 percent. However, with an additional budget of $20,000 (4.5 percent increase), the quality can be increased to 0.935 (8.5 percent improvement). Research limitations/implications The present research work is limited to project objectives of time, cost and quality. Future expansion of the model will focus on additional project objectives such as safety and sustainability. Furthermore, new optimization models can be developed for construction projects with repetitive nature such as roads, tunnels and high rise buildings. Practical implications The present model advances existing research in planning construction projects efficiently and achieving important project objectives. On the practical side, the optimization model will support the construction industry by allowing construction managers to identify the highest quality to deliver a construction project within specified budget and duration, lowest cost for specified duration and quality or shortest duration for specified budget and quality. Originality/value The present model introduces new and innovative method of increasing working hours per day and number of working days per shift while analyzing labor working efficiency and overtime rate to identify optimal trade-offs among important project objectives of time, cost and quality.

Knowledge acquisition based on improved PSO algorithm and entropy

2009 ◽  
Vol 29 (8) ◽  
pp. 2245-2249 ◽  
Author(s):  
Xiang XU ◽  
Dong-bo ZHANG ◽  
Hui-xian HUANG ◽  
Zi-wen LIU
Keyword(s):  
Knowledge Acquisition ◽  
Pso Algorithm ◽  
Improved Pso
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