A hybrid algorithm for a class of resource constrained scheduling problems

Authors:
Yingyi Chu;Quanshi Xia
Affiliations:
IC-Parc, Imperial College London, London, UK;IC-Parc, Imperial College London, London, UK
Venue:
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2005

Citing 4
Cited 2

Constraint-Based Scheduling

Constraint-Based Scheduling
Probe Backtrack Search for Minimal Perturbation in DynamicScheduling

Constraints
Branch-and-Check: A Hybrid Framework Integrating Mixed Integer Programming and Constraint Logic Programming

CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems

INFORMS Journal on Computing

Integrated airline scheduling

Computers and Operations Research
A cutting plane approach for integrated planning and scheduling

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a hybrid algorithm for a class of resource constrained scheduling problems based on decomposition. The general minimum completion time problem is considered, which has not been solved in a decomposed way by existing methods. The problem is first decomposed into an assignment master problem and a number of scheduling subproblems. The subproblem is formulated as both a constraint programming model and an integer programming model. The hybrid algorithm then combines constraint programming, integer programming and linear programming solvers in its three steps: the master problem solving, the subproblems solving and the cut generation. In particular, the cut generation method is based on the integer programming model, and in practice it is done by solving a linear program. Computational experiments have been carried out for the considered minimum completion time problems. The results show that the proposed algorithm could substantially reduce the solving time, compared with directly solving by mixed integer solvers.