An evolutionary parallel tabu search approach for distribution systems reinforcement planning
In this paper a new meta-heuristic optimisation technique is proposed. The method is based on the Parallel Tabu Search (PTS) algorithm and the application is the optimal electrical distribution systems reinforcement planning through the installation of photovoltaic plants, parallel cables, capacitor banks and transformers. The issue is a combinatorial optimisation problem; the objective function is a non-linear expression of a large number of variables. In these cases, meta-heuristics have proved to work well and one of the most efficient is the Tabu Search algorithm. For large-scale problems, parallelisation improves Tabu Search computational efficiency as well as its exploration ability. In this paper, an enhanced version of PTS, Evolutionary Parallel Tabu Search (EPTS), is proposed. It performs reproduction operators on sub-neighbourhoods directing the search towards more promising areas of the search space. The problem of distribution systems reinforcement planning has been studied in detail and the results of the application show that, the EPTS outperforms the PTS and Particle Swarm Optimisation algorithms. The algorithm's performance is also tested on mathematical test functions and other properties of the proposed algorithm are examined. (C) 2003 Elsevier Science Ltd. All rights reserved.
parallel tabu search combinatorial optimisation particle swarm optimisation evolutionary computation optimal planning of distribution systems