Evolutionary hybrid approaches for a power system scheduling problem

K. Dahal, C. Aldridge, S.J. Galloway

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Generation scheduling (GS) in power systems is a tough optimisation problem which continues to present a challenge for efficient solution techniques. The solution is to define on/off decisions and generation levels for each electricity generator of a power system for each scheduling interval. The solution procedure requires simultaneous consideration of binary decision and continuous variables. In recent years researchers have focused much attention on developing new hybrid approaches using evolutionary and traditional exact methods for this type of mixed-integer problems. This paper investigates how the optimum or near optimum solution for the GS problem may be quickly identified. A design is proposed which uses a variety of metaheuristic, heuristics and mathematical programming techniques within a hybrid framework. The results obtained for two case studies are promising and show that the hybrid approach offers an effective alternative for solving the GS problems within a realistic timeframe.
Original languageEnglish
Pages (from-to)2050-2068
Number of pages18
JournalEuropean Journal of Operational Research
Issue number3
Early online date25 Jan 2006
Publication statusPublished - 16 Mar 2007


  • evolutionary computations
  • genetic algorithms
  • knowledge-based systems
  • power systems
  • scheduling

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