篢ransmission network optimal planning prob-lem is a nonlinear, large scale combinatorial optimizationproblem. Although this problem has been extensively stud-ied, it is still not well solved. ln recent years, there is anenormous amount of interest in the applications of Genetic Al-gorithms (GA), Simulated Annealing (SA) and Tabu Search(TS) for solving some difficu1t or poorly characterized opti-mization problems with multi-medal or combinatorial nature.These methods are generally called II... 篢ransmission network optimal planning prob-lem is a nonlinear, large scale combinatorial optimizationproblem. Although this problem has been extensively stud-ied, it is still not well solved. ln recent years, there is anenormous amount of interest in the applications of Genetic Al-gorithms (GA), Simulated Annealing (SA) and Tabu Search(TS) for solving some difficu1t or poorly characterized opti-mization problems with multi-medal or combinatorial nature.These methods are generally called II medern heuristic" tech-niques. The applications of GA and SA in solving the trans-mission network optimal planning problem are reported re-cently. TS is emerging as a new, highly efficient, searchparadigm for quickly finding high quality solutions to combi-natorial optimization problems. It is characterized by gather-ing konwledge during the search, and subsequently profitingfrom this knowledge. In this paper, the authors investigatethe application of TS to the transmission network optimalplanning problem, and develop the mathematical model andsolution algorithm. The test results for three sample systems,although preliminary, have verified the feasibility and effi-ciency of the developed TS based transmission network opti-mal planning method. |