A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

Authors:
José Fernando Gonçalves;Mauricio G. Resende;Jorge J. Mendes
Affiliations:
LIAAD, Faculdade de Economia do Porto, Universidade do Porto, Porto, Portugal 4200-464;Algorithms and Optimization Research Department, AT&T Labs Research, Florham Park, USA 07932;Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Porto, Portugal 4200-072
Venue:
Journal of Heuristics
Year:
2011

Citing 14
Cited 0

Characterization and generation of a general class of resource-constrained project scheduling problems

Management Science
New benchmark results for the resource-constrained project scheduling problem

Management Science
An Exact Algorithm for the Resource-Constrained Project Scheduling Problem Based on a New Mathematical Formulation

Management Science
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
A Tabu Search Approach for the Resource ConstrainedProject Scheduling Problem

Journal of Heuristics
A Hybrid Genetic Algorithm for Assembly Line Balancing

Journal of Heuristics
Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements

Management Science
Solving Project Scheduling Problems by Minimum Cut Computations

Management Science
On the generation of circuits and minimal forbidden sets

Mathematical Programming: Series A and B
An evolutionary algorithm for manufacturing cell formation

Computers and Industrial Engineering
A hybrid genetic algorithm for the weight setting problem in OSPF-IS-IS routing

Networks
Complex Scheduling (GOR-Publications)

Complex Scheduling (GOR-Publications)
Constraint-Propagation-Based Cutting Planes: An Application to the Resource-Constrained Project Scheduling Problem

INFORMS Journal on Computing
A random key based genetic algorithm for the resource constrained project scheduling problem

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.