Multiobjective Enterprise Partner Selection Model with Different Relative Superiority Parameters Based on Particle Swarm Optimization This paper studies a multiobjective virtual enterprise partner selection model with relative superiority parameter in fuzzy environment. The objective of the model is to maximize customersxe2x80x99 minimum satisfaction index, maximize average customer satisfaction index and minimize project completion cost. The completion time and delivery time are fuzzily processed. By means of relative superiority degree and weighting, the multiobjective model is transformed into a singleobjective model and solved by particle swarm optimization (PSO). Finally, a specific example is given to solve the problem. The results of example show that there are different influences on the optimal solution and objective function value as to different relative superiority degrees and different weights.

Maintenance Optimization of Consecutive k outof n System with Multiobjective Birnbaum Importancebased Particle Swarm Optimization This paper focuses on the maintenance optimization problem of consecutivekoutofn systems which are maintained through exchanging the position of components and improving the reliability of components. At first, the multiobjective maintenance optimization model is constructed based on comprehensive consideration of the system reliability and maintenance cost. Then, the relationship between component reliability and maintenance cost is discussed and introduced into the Birnbaum importance to establish the idea of multiobjective Birnbaum importance (MOBI). It is clear that the maintenance strategy based on MOBI was more effective than the maintenance strategy based on traditional Birnbaum importance. Thirdly, the MOBIbased particle swarm optimization (MOBIPSO) method is proposed by taking the advantages of MOBI and particle swarm optimization. Finally, the MOBIPSO is applied to solve the problem of multiobjective maintenance optimization for consecutivekoutofn systems. The simulation results show that the optimization algorithm based on MOBI could make the system more reliable with lower maintenance cost after maintenance.