Optimal parameter selection problem with application to the synchronization of delivery cycles in a supply chain with Wiener process

2019 ◽  
Vol 40 (5) ◽  
pp. 914-937 ◽  
Author(s):  
Kar Hung Wong ◽  
Chi Kin Chan ◽  
Y. C. E. Lee
Keyword(s):  
Supply Chain ◽  
Wiener Process ◽  
Optimal Parameter ◽  
Parameter Selection ◽  
Selection Problem ◽  
Optimal Parameter Selection

scholarly journals On constrained stochastic optimal parameter selection problems

1990 ◽  
Vol 41 (3) ◽  
pp. 393-405 ◽  
Author(s):  
C.J. Goh ◽  
K.L. Teo
Keyword(s):  
State Constraints ◽  
Optimal Parameter ◽  
Parameter Selection ◽  
The State ◽  
Selection Problem ◽  
Numerical Examples ◽  
Selection Problems ◽  
Probability Constraints ◽  
Time Invariant ◽  
Optimal Parameter Selection

This paper considers a special class of stochastic optimal parameter selection problem subject to probability constraints on the state. The system dynamics are governed by a linear Ito stochastic differential equation with controllable parameters appearing nonlinearly in the dynamics. The problem seeks to optimise a cost functional which is quadratic in the state with weighting matrices being time invariant but depending nonlinearly on the parameters. Although the inclusion of the probability state constraints renders the problem insolvable by the conventional LQG theory, we show that the problem can in fact be transformed into an equivalent deterministic optimal parameter selection problem solvable by an existing software MISER. Numerical examples are presented to demonstrate the feasibility and efficiency of the proposed approach.

scholarly journals Tracking control of linear switched systems

2007 ◽  
Vol 49 (2) ◽  
pp. 187-203 ◽  
Author(s):  
R. Li ◽  
Z.G. Feng ◽  
K.L. Teo ◽  
G.R. Duan
Keyword(s):  
Cost Function ◽  
Switched Systems ◽  
Optimal Parameter ◽  
Parameter Selection ◽  
Selection Problem ◽  
Control Input ◽  
Tracking Problem ◽  
Filled Function ◽  
Switching Times ◽  
Optimal Parameter Selection

AbstractThis paper deals with the optimal tracking problem for switched systems, where the control input, the switching times and the switching index are all design variables. We propose a three-stage method for solving this problem. First, we fix the switching times and switching index sequence, which leads to a linear tracking problem, except different subsystems are defined in their respective time intervals. The optimal control and the corresponding cost function obtained depend on the switching signal. This gives rise to an optimal parameter selection problem for which the switching instants and the switching index are to be chosen optimally. In the second stage, the switching index is fixed. A reverse time transformation followed by a time scaling transform are introduced to convert this subproblem into an equivalent standard optimal parameter selection problem. The gradient formula of the cost function is derived. Then the discrete filled function is used in the third stage to search for the optimal switching index. On this basis, a computational method, which combines a gradient-based method, a local search algorithm and a filled function method, is developed for solving this problem. A numerical exampleis solved, showing the effectiveness of the proposed approach.

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