Abstract
An improved genetic-tabu search algorithm is proposed in this paper, which combines large scale search ability of genetic algorithm (GA) and anti-premature ability of tabu search (TS). A long term memory list is designed to record elite solutions searched by GA operation (GA-LTM), and those solutions are induced to each crossover procedure, and drive offspring close to the optimum value. After certain iterations of GA operation, local optimum solutions in solution space are recorded in the GA-LTM. Then, GA operations stop, and solutions in GA-LTM are adopted as start points of TS algorithm. For each solution in GA-LTM, TS search procedure initializes with a trace-back strategy. If TS cannot find better solutions after several steps, the best solution found in previous steps would be recorded as best solution for the start point. After TS search for solutions in GA-LTM accomplish, a comparison is made among those TS found solutions, and the best one is recognized as the optimum solution. At end of this paper, a simulation study on 5 thermal units is done. Validity of the proposed algorithm is approved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
