Genetic Algorithm-Based Searching Method for Piping Path Routing in Coal-Fired Boiler Buildings

Power plant design using digital engineering based on 3-D computer-aided design has become a mainstream technology because of possessing higher speed and improvement in design accuracy. To take a coal-fired boiler building as an example, it has many complex structures with several million parts including the boiler itself, large fans, steel structures, and piping in varying sizes. Therefore, it is not easy to maintain integrity of the whole design throughout all the many engineering processes. We have developed a smart design system for coal-fired boiler buildings to solve the integrity problem. This system is capable of creating and allocating 3-D models automatically in accordance with various technical specifications and engineering rules. Lately, however, there has been a growing demand for more effectiveness of the developed system. We have begun to look into the feasibility of further improvements of the system function. The first point to note, when considering effectiveness, is the piping path routing process in the coal-fired boiler building. The quantity of piping is large, and it has a considerable impact on performance of the whole plant because hot steam is fed into the steam turbine and cold steam is taken from it through the piping. A considerable number of studies have been made on automatic searching methods of piping path routing. Although, the decision of piping path routing by using the Dynamic Programming method is most commonly, a previously decided routing becomes an interference object because of the single searching method. Therefore, basically, the later the order of the routing becomes, the longer the length of the routing becomes. To overcome this problem, in this paper we have proposed a new searching method based on the Genetic Algorithm (GA). The GA is a multipoint searching algorithm based on the mechanics of natural selection and natural genetics. Virtual prohibited cells are introduced into the proposed search method as a new idea. The virtual prohibited cells are located in a search space. The different paths are generated by avoiding the virtual prohibited cells while searching for the piping path routing. The optimum locations of the prohibited cells which are expressed in a genotype are obtained by using the GA in order to get a lot of paths independent of the order of the routing. The proposed method was evaluated using a simple searching problem. The results showed that many effective paths are generated by making the virtual prohibited cells.