Browsing by Author "Mendes, J. J. M."
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- A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problemPublication . Gonçalves, J. F.; Resende, M. G. C.; Mendes, J. J. M.This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.
- A genetic algorithm for the resource constrained multi-project scheduling problemPublication . Gonçalves, J. F.; Mendes, J. J. M.; Resende, M. G. C.This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.
- A Hybrid Genetic Algorithm for the Job Shop Scheduling ProblemPublication . Gonçalves, José Fernando; Mendes, J. J. M.; Resende, Maurício G. C.This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.
- A random key based genetic algorithm for the resource constrained project scheduling problemPublication . Mendes, J. J. M.; Gonçalves, J. F.; Resende, M. G. C.This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.