Genetic algorithm and universal generating function technique for solving problems of power system reliability optimization

2002 ◽  
Author(s):  
G. Levitin ◽  
A. Lisnianski ◽  
H.B. Haim ◽  
D. Elmakis
Keyword(s):  
Genetic Algorithm ◽  
Power System ◽  
Generating Function ◽  
System Reliability ◽  
Function Technique ◽  
Power System Reliability ◽  
Reliability Optimization ◽  
System Reliability Optimization ◽  
Universal Generating Function

Complex Mechatronic System Reliability Optimization Using Hybrid Genetic Algorithm

2011 ◽  
Vol 138-139 ◽  
pp. 1296-1301 ◽  
Author(s):  
J. C. Wang ◽  
H. Qiu ◽  
J. M. Chen ◽  
G. D. Ji
Keyword(s):  
Genetic Algorithm ◽  
System Reliability ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Optimization Techniques ◽  
Reliability Optimization ◽  
Mechatronic System ◽  
Reliability Allocation ◽  
Highly Nonlinear ◽  
System Reliability Optimization

Reliability allocation optimization problem of a complex mechatronic system is a highly nonlinear constrained optimization problem, and hence solution to this kind of problem is of NP-hardness even with moderate scale. Due to the nonlinearity combined with multiple local extreme values, traditional optimization techniques fail to arrive at the global or nearly global optimal solution to the problem. Genetic algorithm incorporated with neighboring domain traversal searching technique is utilized in this paper to solve the complex mechatronic system reliability optimization allocation problem. Reliability allocation optimization of the life-support system in a space capsule, being a typical non serial-parallel system, is specifically demonstrated to show the satisfactory convergence performance as well as the important practical value of hybrid genetic algorithm. The simulation results show that the proposed method may gain better precision in solving the complex mechatronic system reliability optimization problem.

OPTIMAL ALLOCATION OF MULTISTATE ELEMENTS IN LINEAR CONSECUTIVELY-CONNECTED SYSTEMS WITH DELAYS

2002 ◽  
Vol 09 (01) ◽  
pp. 89-108 ◽  
Author(s):  
GREGORY LEVITIN
Keyword(s):  
Genetic Algorithm ◽  
Generating Function ◽  
System Reliability ◽  
Function Method ◽  
Optimal Allocation ◽  
Allocation Problem ◽  
Time Period ◽  
Different Characteristics ◽  
Universal Generating Function

A linear consecutively-connected system consists of N + 2 linear ordered positions. The first position contains a source of a signal and the last one contains a receiver. M statistically independent multistate elements (retransmitters) with different characteristics are to be allocated at the N intermediate positions. The elements provide retransmission of the received signal to the next few positions. Each element can have different states determined by a number of positions that are reached by the signal generated by this element. The probability of each state for any given element depends on the position where it is allocated. The signal retransmission process is associated with delays. The system fails if the signal generated by the source can not reach the receiver within a specified time period. A problem of finding an allocation of the multistate elements that provides the maximal system reliability is formulated. An algorithm based on the universal generating function method is suggested for the system reliability determination. This algorithm can handle cases where any number of multistate elements are allocated in the same position while some positions remain empty. It is shown that such an uneven allocation can provide greater system reliability than an even one. A genetic algorithm is used as an optimization tool in order to solve the optimal element allocation problem.

A Reliability Optimization Allocation Method for Multifunction System With Differentiation of Functions

2015 ◽  
Author(s):  
Xiaojian Yi ◽  
Peng Hou ◽  
Haiping Dong ◽  
Yuehua Lai ◽  
Huina Mu
Keyword(s):  
Genetic Algorithm ◽  
Generating Function ◽  
System Reliability ◽  
Reliability Optimization ◽  
Main Function ◽  
System Function ◽  
Improved Genetic Algorithm ◽  
Reliability Allocation ◽  
Power Shift ◽  
Optimization Allocation

The study on the optimization of system reliability allocation rarely involved the constraints on different functions of system. Some constraints only referred to the main function or one function in system. Owing to the requirement of mission and other factors, all system functions need to have different performance and reliability respectively. For this reason, we proposed a new method for optimization of reliability allocation in this paper. The constrains in the method focus on the discrepancy of reliability of different functions of system. The reliability of system function is defined as it whether to meet the requirement of mission capacity, and the reliability of all different system functions will be calculated by universal generating function, and the objective is to minimize system cost. At last, this method is applied in reliability optimization allocation of a Power-shift Steering Transmission with the improved genetic algorithm.

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