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Bagherinejad, Jafar, Jolai, Fariborz, Rafiee Majd, Zahra. (1392). Solving the MRCPSP/Max with the Objective of Minimizing Tardiness Costs and Maximizing Earliness Rewards of Activities with a Two-stage Genetic Algorithm. , 47(1), 1-13. doi: 10.22059/jieng.2013.35506
Jafar Bagherinejad; Fariborz Jolai; Zahra Rafiee Majd. "Solving the MRCPSP/Max with the Objective of Minimizing Tardiness Costs and Maximizing Earliness Rewards of Activities with a Two-stage Genetic Algorithm". , 47, 1, 1392, 1-13. doi: 10.22059/jieng.2013.35506
Bagherinejad, Jafar, Jolai, Fariborz, Rafiee Majd, Zahra. (1392). 'Solving the MRCPSP/Max with the Objective of Minimizing Tardiness Costs and Maximizing Earliness Rewards of Activities with a Two-stage Genetic Algorithm', , 47(1), pp. 1-13. doi: 10.22059/jieng.2013.35506
Bagherinejad, Jafar, Jolai, Fariborz, Rafiee Majd, Zahra. Solving the MRCPSP/Max with the Objective of Minimizing Tardiness Costs and Maximizing Earliness Rewards of Activities with a Two-stage Genetic Algorithm. , 1392; 47(1): 1-13. doi: 10.22059/jieng.2013.35506

Solving the MRCPSP/Max with the Objective of Minimizing Tardiness Costs and Maximizing Earliness Rewards of Activities with a Two-stage Genetic Algorithm

Advances in Industrial Engineering
مقاله 1، دوره 47، شماره 1، تیر 2013، صفحه 1-13    اصل مقاله (620.25 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jieng.2013.35506
نویسندگان
Jafar Bagherinejad* 1؛ Fariborz Jolai2؛ Zahra Rafiee Majd1
1Dept. Of Industrial Engineering, Faculty of Engineering and Technology, University of ALzahra, Tehran, I.R. Iran
2School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, I.R. Iran
چکیده
In this study, we present a MRCPSP/max (Multi-mode Resource-Constrained Project Scheduling Problem with Minimum and Maximum time lags) model with minimization tardiness costs and maximization earliness rewards of activities as objective. The proposed model is nearby to real-world problems and has wide applications in various projects. This problem is not available in the literature exactly and we developed it for the first time. In order to solve this problem, we developed a two-stage genetic algorithm. In the first stage, the main problem is simplified, through applying a genetic algorithm, in which each activity has only one executive mode.  In the second phase, with developing another genetic algorithm, the best answer of the problem is achieved. Each phase has its own codification, fitness function, crossover operator and mutation operator. Finally, the computational results obtained from the algorithms of this research, which was written in MATLAB programming language, was compared with the results existing in the project scheduling problems library (PSPLIB). The findings show that, our algorithm improved some of the best solutions, recorded in the PSPLIB.
کلیدواژه‌ها
Project scheduling؛ Multi- mode activities؛ Minimum and maximum time lags؛ Two-stage genetic algorithm
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