Max-min ant system applied in economic load dispatch

Authors:
Aristidis Vlachos;Aspasia Moue
Affiliations:
Department of Informatics, University of Piraeus, Piraeus, Greece;Physical Chemistry Laboratory, Department of Chemical Engineering, National Technical University of Athens, Athens, Greece
Venue:
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
Year:
2005

Citing 5
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Abstract

This paper presents a new approach to Economic Load Dispatch (ELD) problems using the Max-Min Ant System Optimization. Historically, traditional optimizations techniques have been used, such as linear and non-linear programming, but within the past decade the focus has shifted on the use of Evolutionary Algorithms, for example Genetic Algorithms, Simulated Annealing and more recently Ant Colony Optimization (ACO). In this paper we introduce the Max-Min Ant System based version of the Ant System. This algorithm encourages local searching around the best solution found in each iteration. To show its efficiency and effectiveness, the proposed Max-Min Ant System is applied to sample ELD problems composed of 4 generators. Comparison to conventional genetic algorithms is presented.