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1 2020

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A hybrid algorithm based on non-dominated sorting ant colony and genetic algorithmsfor solving multi-objective multi-mode project scheduling problems under resource constraints

Bagherinejad Jafar, Jolai Fariborz, Abdollahnejad Raheleh, Shoeib Mahnaz

Management and Production Engineering Review

2020

Vol. 11, No. 2

88--98

A project scheduling problem investigates a set of activities that have to be scheduled due to precedence priority and resource constraints in order to optimize project-related objective functions. This paper focuses on the multi-mode project scheduling problem concerning resource constraints (MRCPSP). Resource allocation and leveling, renewable and non-renewable resources, and time-cost trade-oﬀ are some essential characteristics which are considered in the proposed multi-objective scheduling problem. In this paper, a novel hybrid algorithm is proposed based on non-dominated sorting ant colony optimization and genetic algorithm (NSACO-GA). It uses the genetic algorithm as a local search strategy in order to improve the eﬃciency of the ant colony algorithm. The test problems are generated based on the project scheduling problem library (PSPLIB) to compare the eﬃciency of the proposed algorithm with the non-dominated sorting genetic algorithm (NSGA-II). The numerical result veriﬁes the eﬃciency of the proposed hybrid algorithm in comparison to the NSGA-II algorithm.