基于免疫遗传微粒群智能算法的工程项目多目标优化研究

发布时间：2018-06-13 20:34

本文选题：工程项目 + 多目标优化　；参考：《中国石油大学(华东)》2014年硕士论文

【摘要】：随着改革、开放的不断向前推进,工程项目逐渐趋向大型化、复杂化、系统化,目标维度不断扩大。新的问题、新的目标、新的要求、新的标准不断出现,以适应经济与社会发展的需求。过去的工程管理理念与管理技术落后于经济和社会发展,这需要不断总结前人的经验、研究新的问题,使用新的方法、新的理论对工程项目多目标优化问题进行研究。本文继承与总结前人在工程项目多目标优化研究中取得的成果,利用近年来智能算法所取的成就,对工程管理领域出现的新问题进行探索性研究。通过分析微粒群智能算法(PSO)、免疫智能算法、遗传智能算法各自的优缺点,构建本文的免疫遗传微粒群智能算法(IGPSO)模型。对前人在工程管理领域研究中所取得经验和成果进行总结和借鉴,构建基于工程项目集成管理理论、时间与成本关系、价值工程理论、混联系统可靠性理论、建筑工程环境评价理论体系的“工期-质量-成本-安全-环境”多目标优化模型。在论文的后半部分,将所构建的算法理论与所建立的工程项目多目标优化模型共同运用于具体例子中,进行优化分析和检验。希望通过新理论、新方法的运用能够对以后的研究有所启示。同时,从检验结果上看本文的基于IGPSO的工程项目集成管理多目标优化研究达到了预期效果。
[Abstract]:With the reform and the development of opening up, the project tends to be large, complex, systematic and the goal dimension is expanding. New problems, new goals, new requirements, new standards are emerging to meet the needs of economic and social development. In the past, the concept and technology of engineering management lagged behind the development of economy and society. It is necessary to sum up the previous experiences, study new problems, use new methods and new theories to study the multi-objective optimization problems of engineering projects. This paper inherits and summarizes the achievements made by predecessors in the research of multi-objective optimization of engineering projects, and makes use of the achievements of intelligent algorithms in recent years to carry out exploratory research on new problems in the field of engineering management. By analyzing the advantages and disadvantages of PSO, immune intelligent algorithm and genetic intelligent algorithm, the model of immune genetic particle swarm intelligent algorithm (IGPSO) in this paper is constructed. Based on the theory of integrated management of engineering project, the relationship between time and cost, the theory of value engineering, and the reliability theory of hybrid system, the author summarizes and draws lessons from the experiences and achievements made by predecessors in the field of engineering management. The multi-objective optimization model of time-quality-cost-safety-environment of environmental evaluation system of construction engineering. In the second half of this paper, the algorithm theory and the multi-objective optimization model of engineering project are used in the concrete example to analyze and test the optimization. It is hoped that the application of the new method can enlighten the future research through the new theory. At the same time, from the test results, the IGPSO-based project integrated management multi-objective optimization research has achieved the desired results.
【学位授予单位】：中国石油大学(华东)
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU71;TP18

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