The Research Of The Resource Optimization In Engineering Network

Resource optimization is considered as a highly important content to the scheduling of the project management. A suitable resource arrangement not only brings a huge facility for organizing management of the construction, but also achieves much benefit economically for the builder during the construction. The research of resource optimization in the early stage is mostly based on the analysis and the heuristics method. However, these methods pose a great many problems such as the low calculation efficiency, the poor transplantation, and the monotonous results;meanwhile the methods have many requirements for the goal questions. As for these problems resulted from the analysis and the heuristics method, another two methods (namely particle swarm algorithm and the random search algorithm) are applied for the resource optimization in this paper.Particle swarm algorithm is a new optimization approach that developed recently. Compared with the analysis and the heuristics method, the particle swarm algorithm has a quicker rate of convergence, higher accuracy and the better global convergence ability. Furthermore it has little requirement to the goal questions with better transplantation. The author defines a variable to denote the estate of the activities, establishes the evaluation function whose independent variable was the actual start time of the activities, makes the further improvement to the optimization foundation, and presents a new optimization based on the dynamic float of the noncritical activities in the paper. The particle swarm algorithm is firstly applied to the unlimited leveling optimization problem which obtains satisfactory results.Like the particle swarm algorithm does, the random search algorithm is another approach that needs little requirements to goal question with good commonality. It builds the sub-aggregate of the feasible solution of the goal problem by the homogeneous random numbers and searches the best solution in this finitude sub-aggregate as the approximate optimization solution for the goal problem. The usage of this method to the unlimited leveling optimization problem achieves a better outcome too.For the resource-constraned project scheduling problem, the author presents a new conception called the random priority to differentiate the precedence relationship of the activities in parallel relationship, and constructs the activity sequences of the network by combining the random priority with the topology sort, than uses the random search algorithm to find the optimization solution in this paper. It indicates that this method is better than theheuristics method through the results, and makes up the monotonous and the poor transplantation characters for the heuristics method.By the comparison of the results, it indicates that the two new methods are feasible and contain many advantages over other methods. The two methods applied in this paper are applicable to the solution of the resource optimization problems and reveal the practical value for the project management.