Author(s)

Huaping He

Corresponding Author

Huaping He

ABSTRACT

According to the rules of the game, the linear programming model, multi-objective optimization model and intelligent algorithm in operational research are used to solve the problems of resource carrying and maximum profit. The first and second levels have the same data except different maps, so they are abstracted to solve general problems. When the weather is known, to seek the maximum benefit, first simplify the map, build the shortest path model, and find the shortest path from the starting point to the mine and village with the help of the toolbox in MTATLAB; According to the known conditions, the single objective function and related linear constraints are determined and solved by simplex method; Finally, we get the following conclusion: if players want to achieve the maximum profit under the first and second level, they must adopt the strategy of starting point to mine and supplying in the village, at the same time, the mining days reach 8 days in the first level and 11 days in the second level, at this time, the optimal profits of the first and second level are 11880 and 11275 yuan. According to weather information, assuming that the distribution of weather obeys multi-item distribution, Bayesian method and maximum likelihood estimation in mathematical statistics are used to determine the parameters of multi-item distribution, pseudo-random is used to simulate the distribution of weather, and finally Monte Carlo algorithm is used to choose strategies and test the feasibility of the model, it is concluded that the third level strategy is to go to the end point directly without mining as the optimal solution, and the fourth level strategy is to start from the mine and supply it twice before leaving, and supply 246 boxes of food and 235 boxes of water for the first time.

KEYWORDS

Optimal control theory, Monte Carlo algorithm, cellular automata, Bayesian statistics