Farazmand, N., Beheshtinia, M. (2018). Multi-objective optimization of time-cost-quality-carbon dioxide emission-plan robustness in construction projects. Journal of Industrial and Systems Engineering, 11(3), 102-125.

Nahid Farazmand; Mohammadali Beheshtinia. "Multi-objective optimization of time-cost-quality-carbon dioxide emission-plan robustness in construction projects". Journal of Industrial and Systems Engineering, 11, 3, 2018, 102-125.

Farazmand, N., Beheshtinia, M. (2018). 'Multi-objective optimization of time-cost-quality-carbon dioxide emission-plan robustness in construction projects', Journal of Industrial and Systems Engineering, 11(3), pp. 102-125.

Farazmand, N., Beheshtinia, M. Multi-objective optimization of time-cost-quality-carbon dioxide emission-plan robustness in construction projects. Journal of Industrial and Systems Engineering, 2018; 11(3): 102-125.

Multi-objective optimization of time-cost-quality-carbon dioxide emission-plan robustness in construction projects

Today, the construction industry is facing intense competition and success in this competition depends on several factors. Project managers try to minimize project time and cost, carbon dioxide emission and at the same time maximizing the quality of project and its plan robustness. In this paper, study construction project scheduling considering a discrete trade-off between time, cost, quality, carbon dioxide emission and the plan robustness. After presenting the mathematical model of the problem, a genetic algorithm inspired from the role model concept in sociology named Reference Group Genetic Algorithm (RGGA) is used to solve the problem. The “reference group” concept is introduced by a sociologist named Robert K. Merton. He believed that some people in each society such as heroes or entertainment artists affect other people. To evaluate the impact of “reference group” concept in genetic algorithm, RRGA is compared with a similar genetic algorithm that do not use this concept. The originality of this paper is introducing a new multi-objective project scheduling problem, presenting its mathematical model and adapting RGGA to solve it. The computational experiments show that using this concept improves the result.

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