A Near-Optimal Control Policy in Cloud Systems with Renewable Sources and Time-Dependent Energy Price

2018 ◽  
Author(s):  
Jiashang Liu ◽  
Joohyun Lee ◽  
Ness B. Shroff ◽  
Prasun Sinha ◽  
Sinong Wang
Keyword(s):  
Optimal Control ◽  
Control Policy ◽  
Time Dependent ◽  
Energy Price ◽  
Renewable Sources ◽  
Cloud Systems

An optimal control policy to realize green cloud systems with SLA-awareness

2014 ◽  
Vol 69 (3) ◽  
pp. 1284-1310 ◽  
Author(s):  
Yen-Chieh Ouyang ◽  
Yi-Ju Chiang ◽  
Ching-Hsien Hsu ◽  
Gangman Yi
Keyword(s):  
Optimal Control ◽  
Control Policy ◽  
Cloud Systems ◽  
Green Cloud

scholarly journals Mathematical Modeling and Optimal Control of the Hand Foot Mouth Disease Affected by Regional Residency in Thailand

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2863
Author(s):  
Napasool Wongvanich ◽  
I-Ming Tang ◽  
Marc-Antoine Dubois ◽  
Puntani Pongsumpun
Keyword(s):  
Optimal Control ◽  
Numerical Solutions ◽  
Foot And Mouth Disease ◽  
Control Policy ◽  
Mouth Disease ◽  
Sensitivity Analyses ◽  
Urban Region ◽  
Control Parameters ◽  
Control Effort ◽  
Logarithmic Relationship

Hand, foot and mouth disease (HFMD) is a virulent disease most commonly found in East and Southeast Asia. Symptoms include ulcers or sores, inside or around the mouth. In this research, we formulate the dynamic model of HFMD by using the SEIQR model. We separated the infection episodes where there is a higher outbreak and a lower outbreak of the disease associated with regional residency, with the higher level of outbreak occurring in the urban region, and a lower outbreak level occurring in the rural region. We developed two different optimal control programs for the types of outbreaks. Optimal Control Policy 1 (OPC1) is limited to the use of treatment only, whereas Optimal Control Policy 2 (OPC2) includes vaccination along with the treatment. The Pontryagin’s maximum principle is used to establish the necessary and optimal conditions for the two policies. Numerical solutions are presented along with numerical sensitivity analyses of the required control efforts needed as the control parameters are changed. Results show that the time tmax required for the optimal control effort to stay at the maximum amount umax exhibits an intrinsic logarithmic relationship with respect to the control parameters.

scholarly journals Optimal control policy for a Brownian inventory system with concave ordering cost

2015 ◽  
Vol 52 (4) ◽  
pp. 909-925 ◽  
Author(s):  
Dacheng Yao ◽  
Xiuli Chao ◽  
Jingchen Wu
Keyword(s):  
Optimal Control ◽  
Brownian Motion ◽  
Cost Optimization ◽  
Control Policy ◽  
Optimization Criterion ◽  
Inventory System ◽  
Single Pair ◽  
Normal Density ◽  
Strong Condition ◽  
Demand Distribution

In this paper we consider an inventory system with increasing concave ordering cost and average cost optimization criterion. The demand process is modeled as a Brownian motion. Porteus (1971) studied a discrete-time version of this problem and under the strong condition that the demand distribution belongs to the class of densities that are finite convolutions of uniform and/or exponential densities (note that normal density does not belong to this class), an optimal control policy is a generalized (s, S) policy consisting of a sequence of (si, Si). Using a lower bound approach, we show that an optimal control policy for the Brownian inventory model is determined by a single pair (s, S).

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