A case study of scheduling storage tanks using a hybrid genetic algorithm

This paper proposes the application of a hybrid genetic algorithm (GA) for scheduling storage tanks. The proposed approach integrates GAs and heuristic rule-based techniques, decomposing the complex mixed-integer optimization problem into integer and real-number subproblems. The GA string considers...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation 2001-06, Vol.5 (3), p.283-294
Main Authors: Dahal, K.P., Burt, G.M., NcDonald, J.R., Moyes, A.
Format: Article
Language:English
Subjects:
Applied sciences
Computer aided software engineering
Electronic ballasts
Exact sciences and technology
Filling
Genetic algorithms
Heuristic methods
Integers
Job shop scheduling
Marine vehicles
Operational research and scientific management
Operational research. Management science
Optimization
Petroleum
Ports
Scheduling
Scheduling algorithm
Scheduling, sequencing
Storage tanks
Strings
Water pollution
Water resources
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Summary:This paper proposes the application of a hybrid genetic algorithm (GA) for scheduling storage tanks. The proposed approach integrates GAs and heuristic rule-based techniques, decomposing the complex mixed-integer optimization problem into integer and real-number subproblems. The GA string considers the integer problem and the heuristic approach solves the real-number problems within the GA framework. The algorithm is demonstrated for three test scenarios of a water treatment facility at a port and has been found to be robust and to give a significantly better schedule than those generated using a random search and a heuristic-based approach.
ISSN:1089-778X
1941-0026
DOI:10.1109/4235.930316