Abstract
This study addresses the multi-objective multi-mode resource-constrained project scheduling problem with payment planning where the activities can be done through one of the possible modes and the objectives are to maximize the net present value and minimize the completion time concurrently. Moreover, renewable resources including manpower, machinery, and equipment as well as non-renewable ones such as consumable resources and budget are considered to make the model closer to the real-world. To this end, a non-linear programming model is proposed to formulate the problem based on the suggested assumptions. To validate the model, several random instances are designed and solved by GAMS-BARON solver applying the ε-constraint method. For the high NP-hardness of the problem, we develop two metaheuristics of non-dominated sorting genetic algorithm II and multi-objective simulated annealing algorithm to solve the problem. Finally, the performances of the proposed solution techniques are evaluated using some well-known efficient criteria.
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Acknowledgements
This work was supported in part by International Scientific and Technological Cooperation Project of Dongguan (2016508102011), in part by Science and Technology Planning Project of Guangdong Province (2016A020210142) and in part by Guangdong provincial key platform and major scientific research projects (2017GXJK174).
Funding
Funding was provided by International Scientific and Techological Cooperation Project of Dongguan (Grant No. 2016508102011).
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Tirkolaee, E.B., Goli, A., Hematian, M. et al. Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms. Computing 101, 547–570 (2019). https://doi.org/10.1007/s00607-018-00693-1
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DOI: https://doi.org/10.1007/s00607-018-00693-1
Keywords
- Multi-mode resource-constrained project scheduling problem
- NPV
- Payment planning
- ε-Constraint method
- NSGA-II
- MOSA