American Journal of Civil Engineering and Architecture
ISSN (Print): 2328-398X ISSN (Online): 2328-3998 Website: https://www.sciepub.com/journal/ajcea Editor-in-chief: Dr. Mohammad Arif Kamal
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American Journal of Civil Engineering and Architecture. 2015, 3(3A), 9-16
DOI: 10.12691/ajcea-3-3A-2
Open AccessResearch Article

Discrete Time-Cost Tradeoff Model for Optimizing Multi-Mode Construction Project Resource Allocation

Shuangshuang Nie1, and Jihong Gao1

1Department of Construction Management, Tongji University, Shanghai, China

Pub. Date: August 18, 2015
(This article belongs to the Special Issue Big data analytics in Smart Buildings)

Cite this paper:
Shuangshuang Nie and Jihong Gao. Discrete Time-Cost Tradeoff Model for Optimizing Multi-Mode Construction Project Resource Allocation. American Journal of Civil Engineering and Architecture. 2015; 3(3A):9-16. doi: 10.12691/ajcea-3-3A-2

Abstract

The project scheduling and resource allocation problems have been studied using different optimization methods. The resource leveling problem was proposed to reduce the resource fluctuation and was always studied independently resource constraint problem. For example, resource-constrained project scheduling problem (RCPSP) was proposed to optimize scheduling under resource constraints. This research proposed a new model which integrates the resource leveling problem and resource-constrained time-cost tradeoff problem. The evolutionary multi-objective optimization technique, strength Pareto evolutionary approach II (SPEA II) was applied to calculate the Pareto front of time and cost. The resource leveling measured by the metric, resource release/re-hiring, was converted to resource cost. The analysis of the time complexity of the model showed that the runtime of the algorithm was polynomial times of the number of activities. The results of case testing showed that the model was reasonably accurate in comparison with a proposed baseline model.

Keywords:
project scheduling resource-constrained project scheduling problem resource leveling genetic algorithm optimization strength pareto evolutionary approach II

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