Cost optimization model of exponential Weibull distribution accelerated life simulation

2015 ◽  
pp. 483-486 ◽  
Author(s):  
Y Wang ◽  
D Lu ◽  
X Zhang
Keyword(s):  
Weibull Distribution ◽  
Optimization Model ◽  
Cost Optimization ◽  
Accelerated Life

A cost optimization model for 100% renewable residential energy supply systems

Energy ◽  
2012 ◽  
Vol 48 (1) ◽  
pp. 118-127 ◽  
Author(s):  
Christian Milan ◽  
Carsten Bojesen ◽  
Mads Pagh Nielsen
Keyword(s):  
Optimization Model ◽  
Energy Supply ◽  
Cost Optimization ◽  
Residential Energy ◽  
Supply Systems ◽  
Energy Supply Systems

scholarly journals Design and application of accelerated life test of grating ruler based on step stress loading

2021 ◽  
Vol 336 ◽  
pp. 02027
Author(s):  
Jili Wang ◽  
Qingyu Li ◽  
Xiaocui Zhu ◽  
Cheng Gao ◽  
Yi Li ◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Test Method ◽  
Accelerated Life Test ◽  
Test Scheme ◽  
Life Test ◽  
Test Device ◽  
Typical Application ◽  
Accelerated Life ◽  
Life Model ◽  
Accelerated Life Model

Combined with the actual project, a grating ruler accelerated life test device is designed, which can simulate the actual loads, including temperature, humidity and speed stress. An accelerated life test scheme based on stepped stress loading is proposed, and 6 grating rulers are tested based on time-censored test method. An accelerated life model based on Weibull distribution used for evaluating the lifetime is established. Related experimental techniques also can be typical application cases for innovative practical teaching.

scholarly journals A Cost Optimization Model for Multiresource Leveling Problem without Project Duration Constraint

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Qingyou Yan ◽  
Qian Zhang ◽  
Xin Zou
Keyword(s):  
Optimization Model ◽  
Cost Optimization ◽  
Resource Usage ◽  
Project Duration ◽  
Resource Demand ◽  
Resource Leveling ◽  
Proposed Model ◽  
Liquidated Damages ◽  
The Relationship

The study of traditional resource leveling problem aims at minimizing the resource usage fluctuations and obtaining sustainable resource supplement, which is accomplished by adjusting noncritical activities within their start and finish time. However, there exist limitations in terms of the traditional resource leveling problem based on the fixed project duration. This paper assumes that the duration can be changed in a certain range and then analyzes the relationship between the scarce resource usage fluctuations and project cost. This paper proposes an optimization model for the multiresource leveling problem. We take into consideration five kinds of cost: the extra hire cost when the resource demand is greater than the resource available amount, the idle cost of resource when the resource available amount is greater than the resource demand, the indirect cost related to the duration, the liquidated damages when the project duration is extended, and the incentive fee when the project duration is reduced. The optimal objective of this model is to minimize the sum of the aforementioned five kinds of cost. Finally, a case study is examined to highlight the characteristic of the proposed model at the end of this paper.

scholarly journals Redundancy Optimization of an Uncertain Parallel-Series System with Warm Standby Elements

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Linmin Hu ◽  
Wei Huang ◽  
Guofang Wang ◽  
Ruiling Tian
Keyword(s):  
Optimization Algorithm ◽  
Optimization Model ◽  
Cost Minimization ◽  
Cost Optimization ◽  
Series System ◽  
Uncertain Measure ◽  
Uncertain Variables ◽  
Warm Standby ◽  
Parallel Series ◽  
Redundancy Optimization

The redundancy optimization problem is formulated for an uncertain parallel-series system with warm standby elements. The lifetimes and costs of elements are considered uncertain variables, and the weights and volumes of elements are random variables. The uncertain measure optimization model (UMOM), the uncertain optimistic value optimization model (UOVOM), and the uncertain cost optimization model (UCOM) are developed through reliability maximization, lifetime maximization, and cost minimization, respectively. An efficient simulation optimization algorithm is provided to calculate the objective values and optimal solutions of the UMOM, UOVOM, and UCOM. A numerical example is presented to illustrate the rationality of the models and the feasibility of the optimization algorithm.

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