DSPSO–TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions

This paper proposes a new approach based on particle swarm optimization (PSO) and tabu search algorithm (TSA). This proposed approach is called distributed Sobol PSO and TSA (DSPSO–TSA). In order to improve the convergence characteristic and solution quality of searching process, three mechanisms had been presented. Firstly, the Sobol sequence is applied to generate an inertia factor instead of the existing process. Secondly, a distributed process is used so as to reach the global solution rapidly. arch process is divided to multi-stages and used a short-term memory for recognition the best search history. Finally, to guarantee the global solution, TSA had been activated to adjust the obtained solution of DSPSO algorithm. To show its effectiveness, the proposed DSPSO–TSA is applied to test four case studies of economic dispatch (ED) problem considering nonsmooth and noncontinuous fuel cost functions of generating units. The simulation results obtained from DSPSO–TSA are compared with conventional approaches such as genetic algorithm (GA), TSA, PSO, and others in literatures. The comparison results show that the efficiency of proposed approach can reach higher quality solution and faster computational time than the conventional methods.