Construction project multi-objective optimization method

Abstract

The invention provides a construction project multi-objective optimization method. The construction project multi-objective optimization method comprises the following steps: determining a mathematical model and genetic algorithm parameters of multi-objective optimization; establishing a population with feasible constraints and a population target function matrix; calculating an objective weight of the target function by adopting an entropy weight method according to the target function matrix, and synthesizing a hybrid dynamic weight of the target function; sorting the population by adoptinga method based on dynamic weight to obtain a Pareto temporary solution set; attaching virtual fitness values to individuals according to population individual sorting, and selecting a filial generation population by adopting a proportional selection operator and a roulette method; performing crossover operation on the filial generation population; performing mutation operation on the filial generation population after the crossover operation; combining the Pareto temporary solution set with the filial generation population after mutation operation to generate a new population; and if the algorithm termination condition is met, terminating the algorithm, otherwise, returning. According to the method, the problem of ambiguity between an original multi-objective optimization algorithm and engineering application is well solved, and the method has better engineering applicability.

Description

technical field [0001] The invention belongs to the technical field of management design, in particular to a multi-objective optimization method for construction projects based on an improved genetic algorithm. Background technique [0002] Engineering project management is the management to achieve multi-objective optimization of construction period, cost, quality, safety, environment, etc. With the development of intelligent optimization algorithms, genetic algorithms have been widely used in engineering, and are increasingly used to solve multi-objective optimization question. The people, materials, machines and funds that can be obtained during the construction process of a construction project are limited. Generally speaking, if limited resources can be properly allocated, economic benefits will increase significantly, and optimal allocation is to make better use of resources. Using resource optimization allocation, limited resources can be used to complete project co...

AI Technical Summary

Problems solved by technology

However, in engineering applications, the final use plan is unique. The diversity of the Pareto solution set of the original multi-objective optimization algorithm and the uniqueness of the engineering application plan lead to ambiguity. How to select the most needed design plan in the Pareto solution set It has become another focus of multi-objective optimization problems. In this field, a multi-attribute decision-making method based on analytic hierarchy process and fuzzy comprehensive evaluation has been formed. However, there is no inherent relationship between multi-objective optimization and multi-attribute decision-making. in series

Images