Using dynamic programming to determine an optimal strategy in a contract bridge tournament

2010 ◽  
Vol 61 (5) ◽  
pp. 732-739 ◽  
Author(s):  
N Beaumont
Keyword(s):  
Dynamic Programming ◽  
Optimal Strategy ◽  
Contract Bridge

scholarly journals The treatment of optimizing container transportation dynamic programming and planning

2019 ◽  
Vol 135 ◽  
pp. 02016
Author(s):  
Elena Korchagina ◽  
Andrey Bochkarev ◽  
Pavel Bochkarev ◽  
Sergey Barykin ◽  
Svetlana Suvorova
Keyword(s):  
Mathematical Model ◽  
Dynamic Programming ◽  
Linear Programming ◽  
Numerical Calculation ◽  
Optimal Strategy ◽  
Programming Algorithm ◽  
Container Transportation ◽  
Dynamic Planning ◽  
Railway Freight ◽  
Linear Programming Algorithm

The article addresses the treatment of applying the method of dynamic linear programming to solve the task of choosing the optimal strategy for the containers dispatch, taking into account the significant unevenness of loading and shipment of containers. The optimizing container transportation dynamic planning could be treated as mathematical model of the dynamic multi-period task of the loaded containers shipment, which allows the choice of the optimal strategy for sending containers, taking into account the significant unevenness of their loading and dispatch from the railway freight station. The efficiency of considered method is proved by numerical calculation being presented to disclose the dynamic linear programming algorithm implementing to solve the problem.

A GOLD-MINING PROBLEM

2000 ◽  
Vol 14 (2) ◽  
pp. 151-160
Author(s):  
Minoru Sakaguchi ◽  
Toshio Hamada
Keyword(s):  
Dynamic Programming ◽  
Optimal Strategy ◽  
Gold Mining ◽  
Control Limit ◽  
Limit Property

We study an example of R. Bellman's gold-mining problem related to a programming job on the computer. The problem is formulated by dynamic programming and the optimal strategy is explicitly derived. The Bayesian version when the parameter involved is unknown is also solved by the same method. It is shown that the optimal strategy in each of two versions has the “no-island” (or, in other words, “control-limit”) property.

OPTIMAL STRATEGIES IN ONE-DAY CRICKET

2008 ◽  
Vol 25 (04) ◽  
pp. 495-511 ◽  
Author(s):  
PAM NORTON ◽  
RAVI PHATARFOD
Keyword(s):  
Dynamic Programming ◽  
Optimal Strategy ◽  
Optimal Strategies ◽  
Programming Formulation ◽  
Expected Number ◽  
Maximum Probability ◽  
Subsequent Selection ◽  
Selection Of

Using a dynamic programming formulation, an analysis is presented of both the first and second innings of a one-day cricket match assuming variation in type of ball bowled and subsequent selection of a strategy by the batsman. We assume that the team batting first uses the strategy to maximize the expected score, and the team batting second uses the strategy to maximize the probability of outscoring the first team and thus of maximizing the probability of a win. The dynamic programming formulation allows a calculation, at any stage of the innings, of the optimal scoring strategy depending on the type of ball bowled, along with an estimate of the maximum of the expected number of runs scored in the remainder of the first innings, and the maximum probability of a win in the second innings. Modifications are then introduced to examine the effect of tailender batsmen and a "fifth bowler". Finally a simulation is done to estimate the variance in total score by following the optimal strategy used in the first innings.

Dynamic Programming and Mean-Variance Hedging in Discrete Time

2003 ◽  
Vol 10 (2) ◽  
pp. 237-246
Author(s):  
S. Gugushvili
Keyword(s):  
Dynamic Programming ◽  
Discrete Time ◽  
Optimal Strategy ◽  
Programming Approach ◽  
Dynamic Programming Approach ◽  
The Mean ◽  
Hedging Problem ◽  
Mean Variance

Abstract We consider the mean-variance hedging problem in the discrete time setting. Using the dynamic programming approach we obtain recurrent equations for an optimal strategy. Additionally, some technical restrictions of the previous works are removed.

DYNAMIC PORTFOLIO SELECTION WITH UNCERTAINTY

2009 ◽  
Vol 17 (02) ◽  
pp. 237-250 ◽  
Author(s):  
MEI YU ◽  
HIROSHI INOUE ◽  
SATORU TAKAHASHI ◽  
JIANMING SHI
Keyword(s):  
Dynamic Programming ◽  
Closed Form ◽  
Portfolio Selection ◽  
Financial Market ◽  
Optimal Strategy ◽  
Investment Strategy ◽  
Selection Strategy ◽  
Total Risk ◽  
Dynamic Programming Problem ◽  
Dynamic Portfolio

How to make a prompt decision for uncertainty investment is always a key problem in financial market. In this paper, we present a new dynamic portfolio selection strategy in stock market. The investor is assumed to seek an investment strategy that will maximize his/her final wealth and minimize the total risk. An analytically optimal strategy in closed form is obtained by solving a dynamic programming problem. Some applications are also presented to illustrate this model.

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