Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Journal of Global Optimization
Differential evolution for solving multi-mode resource-constrained project scheduling problems
Computers and Operations Research
A multi-mode resource-constrained scheduling problem in the context of port operations
Computers and Industrial Engineering
A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems
Applied Soft Computing
An exact solution procedure for mode identity and resource constrained project scheduling problem
MATH'10 Proceedings of the 15th WSEAS international conference on Applied mathematics
A genetic algorithm approach to a general category projectscheduling problem
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Expert Systems with Applications: An International Journal
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Mode identity and resource constrained project scheduling problem (MIRCPSP) is a substantial generalization of the well-known multi-mode problem. It arises when certain activities in the project are interdependent. That is, the set of all activities in the project are partitioned into disjoint subsets where all activities forming one subset have to be processed in the same mode. This paper addresses project scheduling problem with resource and mode identity constraints to minimize the project makespan. This problem is strongly NP-hard and three meta-heuristic algorithms namely imperialist competitive algorithm, simulated annealing and differential evolution are proposed to solve it. In order to improve the quality of the employed algorithms a local search and learning module is combined with the meta-heuristic algorithms. The performance of the algorithms is evaluated on 180 test problems by statistically comparing their solution in term of the objective function and computational times. The obtained computational results indicate that the integration of the learning module and the proposed algorithm is efficient and effective.