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Application of Robust Discrete Optimization Theory in Elevator Group Control Systems

Author: WangWeiJia
Tutor: ZongQun
School: Tianjin University
Course: Control Theory and Control Engineering
Keywords: Uncertain optimization Robust discrete optimization Integer Programming Branch and bound method Elevator Group Control Dispatching
CLC: O231
Type: Master's thesis
Year: 2007
Downloads: 30
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Abstract

Uncertain optimization problem has the important significance of the study, a new method of robust optimization optimization problem as a research uncertain, scholars from various countries in recent years has been widespread concern. Thesis, Robust discrete optimization modeling, model transformation and model solving theory. And robust discrete optimization study applied to elevator group scheduling problem. The specific research content of the paper is as follows: The paper first describes the method of the uncertain optimization theory analysis, research significance robust optimization, and robust optimization theory study analyzed the current situation. Uncertain systems optimization theory, the basic principle of robust optimization, and then analyze the the Bertsimas robust optimization theory framework. Focuses on robust discrete optimization theory, given the robust discrete optimization modeling, model transformation, and study the constraints contrary to probability boundary theory. Modeling and Solving robust discrete optimization problem for the practical application of the elevator group scheduling problems. First, a brief introduction of the elevator group scheduling problems, analyzed the existing group control scheduling method, and traffic flow uncertainty of the key issues to be analyzed. On this basis, established based on the the Bertsimas theory elevator group control scheduling robust discrete optimization model to achieve the transformation of the model robust peer-to-peer, the initial uncertainty robust discrete optimization problem into a computational processing mixed 0-1 integer programming problem. Subsequently, in-depth study of the Robust discrete optimization method for solving problems using integer programming methods through comparative analysis of different methods, and ultimately to complete elevator group control scheduling robust discrete optimization problems. The final thesis completed elevator group scheduling algorithm simulation RDO. Of the equation for the robustness of the elevator group scheduling problems, that is a mixed integer programming problem, can make use of auxiliary solving optimization software. Elevator Group Control laboratory already virtual simulation environment, the use of optimization software interface design based on the functions of Elevator Group Control scheduling algorithm robust discrete optimization method, defined algorithm framework. Finally, the simulation results proved that, by comparison with other scheduling algorithms, robust discrete optimization scheduling algorithm has excellent performance and ability to adapt to different traffic shed. The experiments show that the robust discrete optimization scheduling method can solve the traffic flow forecasting error to improve elevator group scheduling performance.

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