Title :
Application of composite particle swarm optimization in reliable design, production, and maintenance planning for multipurpose process plant
Author :
Ren, Ping ; Gao, Liqun ; Zhang, Yang ; Li, Nan
Author_Institution :
Sch. of Inf. Eng., Shenyang Univ., Shenyang
Abstract :
In this paper, reliable design, production, and maintenance planning for multipurpose process plant is formulated as a multi-objective mathematical optimization problem. In this work, five objectives: the total cost of utilities, preventive and corrective maintenance costs, design costs as a function of equipment initial failure rate, and the profit generated by the delivered products are considered in the optimization. To overcome the drawbacks of conventional mathematical optimization method in arriving at local optimum and dimension disasters, etc., we introduce the particle swarm optimization (PSO) technique into reliable design, production, and maintenance planning for multipurpose process plants for the first time, from which the supreme scheme is generated A example on reliable design, production, and maintenance planning for multipurpose process plant is presented to show the feasibility and efficiency of the proposed methodology, compared with the existing optimal planning methods, the search time of the particle swarm optimization method is shorter and the result is close to the ideal solution, simultaneously.
Keywords :
maintenance engineering; particle swarm optimisation; production planning; composite particle swarm optimization; corrective maintenance cost; design costs; dimension disasters; equipment initial failure rate; local optimum; maintenance planning; multiobjective mathematical optimization problem; multipurpose process plant; preventive maintenance cost; production planning; reliable design; utilities cost; Costs; Maintenance; Particle production; Particle swarm optimization; Process planning; Production planning; Composite Particle Swarm Optimization; Maintenance Planning; Multipurpose Process Plan; Production; Reliable Design;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597450