Two-stage ACO to solve the job shop scheduling problem

Authors:
Amilkar Puris;Rafael Bello;Yaima Trujillo;Ann Nowe;Yailen Martínez
Affiliations:
Department of Computer Science, Universidad Central de Las Villas, Cuba;Department of Computer Science, Universidad Central de Las Villas, Cuba;Department of Computer Science, Universidad Central de Las Villas, Cuba;CoMo Lab, Department of Computer Science, Vrije Universiteit Brussel, Belgium;Department of Computer Science, Universidad Central de Las Villas, Cuba
Venue:
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Year:
2007

Citing 9
Cited 1

MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows

New ideas in optimization
Ant algorithms for discrete optimization

Artificial Life
MAX-MIN Ant system

Future Generation Computer Systems
Computers and Intractability: A Guide to the Theory of NP-Completeness

Computers and Intractability: A Guide to the Theory of NP-Completeness
Ant Colony Optimization

Ant Colony Optimization
Ant colony optimization for FOP shop scheduling: a case study on different pheromone representations

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Ant colony system: a cooperative learning approach to the traveling salesman problem

IEEE Transactions on Evolutionary Computation
Ant colony optimization for resource-constrained project scheduling

IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAP

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a multilevel approach of Ant Colony Optimization to solve the Job Shop Scheduling Problem (JSSP) is introduced. The basic idea is to split the heuristic search performed by ants into two stages; only the Ant System algorithm belonging to ACO was regarded for the current research. Several JSSP instances were used as input to the new approach in order to measure its performance. Experimental results obtained conclude that the Two-Stage approach significantly reduces the computational time to get a solution similar to the Ant System.