Modified Adaptive Tabu Search Algorithms for Economic Load Dispatch

AbstractThis paper presents an application of the modified adaptive tabu search algorithms (mATS) to economic load dispatch(ELD). The proposed mATS algorithms with adaptive neighborhood easily handles different constraints like transmission losses, ramp rate limits and also prohibited operating zones. Simulations were divided into two parts, the first part has been set for static economic load dispatch over the six-unit test system and another part for dynamic economic load dispatch (DED) has treated over the five-unit test system with nonsmooth fuel cost function concerning valve point loading effects. Simulation results were a comparison between of the proposed mATS and of the other algorithms including the original ATS, genetic algorithms (GA) and particle swarm optimization (PSO). The findings affirmed the robustness and proficiency of the proposed algorithms overother existing techniques

Performance Evaluation of Modified Adaptive Tabu Search Algorithms and Its Application

AbstractThis paper presents a modified Adaptive Tabu Search Algorithm, namely mATS by adding an adaptive neighborhoodmechanism under the main purpose enhancing search potential of ATS. An application of mATS to the real world problem is tosolving the parameter identification problem of frequency modulation sounds (FMS) which is multimodal and also hard to solveby classical methods. Performance evaluations are elaborated with three surface optimization functions, Bohachevsky’s, Rastrigin’s and Shekel’s foxholes. From the performance test, the results showed that the mATS were faster than those of the original ATS. Moreover, the proposed mATS approach obtained the better quality of the optimal solution than any other methodsof previous works

Multipath Adaptive Tabu Search for a Vehicle Control Problem

Tabu search has become acceptable worldwide as one of the most efficient intelligent searches applied to various real-world problems. There have been different modifications made to the generic tabu search in recent years to achieve better performances. Among those reviewed in the introduction of this paper, the adaptive tabu search (ATS) has incorporated the backtracking and the adaptive search radius mechanisms that help accelerate the search and release it from a local solution lock. The paper explains an enhancement made to the ATS to accomplish multipath ATS (MATS) algorithms. Performances of the ATS and the MATS are evaluated using surface optimization problems, and results are presented in the paper. Finally, the MATS is applied to solve a real-world vehicle control problem