Resource-constrained project scheduling method based on multi-agent evolutionary algorithm

Abstract

The invention discloses a resource-constrained project scheduling method based on a multi-agent evolutionary algorithm, belonging to the technical field of automatic control and information. According to the method, a multi-agent system is combined with evolutionary computation so as to solve the resource-constrained project scheduling problem. The method is characterized by comprising the following steps of: initializing each agent in an agent grid according to two algorithms; and designing a neighborhood competition operator, a neighborhood cross operator, a mutation operator and a self-learning operator for optimizing the agent. The verification result proves that the method has advantages in two aspects for evaluating the effectiveness of the method for solving the resource-constrained project scheduling problem, namely the solving of the optimal solution proportion and the solving of the average error deviating from the optimal solution, so that the method effectively solves the resource-constrained project scheduling problem, and the method can be expanded to solving other combined optimization problems with precedence relationship constraints.

Description

technical field [0001] The invention relates to a method in the field of automatic control and information technology, in particular to a resource-constrained project scheduling method based on a multiagent evolutionary algorithm (MAEA). Background technique [0002] The resource-constrained project scheduling problem (RCPSP for short) widely exists in single-piece or small-batch production enterprises such as construction engineering, software development, aircraft and ship manufacturing, and a reasonable scheduling plan is to reduce costs , Improving quality and shortening the cycle is an important guarantee. RCPSP is not only widely used in practice, but in theory, the problem model is rich, and most of them are NP-hard problems, which are difficult to solve. Therefore, it has always attracted the research and attention of many scholars at home and abroad. [0003] A typical resource-constrained project scheduling problem can be described as: In a project, there are n ta...

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Problems solved by technology

Therefore, using the genetic algorithm to solve resource-constrained project scheduling problems cannot imitate the intelligence of biological processing things very well. In addition, the genetic algorithm also has the disadvantages of premature convergence, slow convergence speed, and poor stability, so that a good project schedule cannot be obtained.

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