Hybrid heuristics for dynamic resource-constrained project scheduling problem

Authors:
André Renato Villela da Silva;Luiz Satoru Ochi
Affiliations:
Universidade Federal Fluminense, Departamento de Ciência da Computação, Niterói, Rio de Janeiro, Brazil;Universidade Federal Fluminense, Departamento de Ciência da Computação, Niterói, Rio de Janeiro, Brazil
Venue:
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
Year:
2010

Citing 5
Cited 1

Efficient parallel cooperative implementations of GRASP heuristics

Parallel Computing
Repairing MIP infeasibility through local branching

Computers and Operations Research
A random key based genetic algorithm for the resource constrained project scheduling problem

Computers and Operations Research
Differential evolution for solving multi-mode resource-constrained project scheduling problems

Computers and Operations Research
New sequential and parallel algorithm for Dynamic Resource Constrained Project Scheduling Problem

IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing

Metaheuristic GRASP with path-relinking to the solution of the graph partitioning problem with capacity and connexity constraints

IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

Dynamic Resource-Constrained Project Scheduling Problem (DRCPSP) is a scheduling problem that works with an uncommon kind of resources: the Dynamic Resources. They increase and decrease in quantity according to the activated tasks and are not bounded like other project scheduling problems. This paper presents a new mathematical formulation for DRCPSP as well as two hybrid heuristics merging an evolutionary algorithm with an exact approach. Computational results show that both hybrid heuristics present better results than the state-of-the-art algorithm for DRCPSP does. The proposed formulation also provides better bounds.